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Startups of The Year 2023 Winners: North America 

RPA Tool Comparison: How to Choose the Right Automation Vendor

You’ve probably noticed this trend of automating tasks, processes, and even entire departments. Maybe, your company is also considering implementing an , but you still haven’t found the answer to the following questions: intelligent process automation solution Do I build a custom system or opt for an off-the-shelf solution? Do I need to prepare my organization for a digital overhaul? If yes, where do I start? In this article, ITRex CEO explains what ready-made and custom enterprise automation solutions can offer and which might better suit your business needs. Vitali also gives tips on getting started with automation and warns of challenges to expect on the way. Vitali Likhadzed What is enterprise automation, and how does it help your company? Definition and terminology clarification Enterprise automation is defined by Integrify as a systematic review of an organization’s processes to ensure optimal performance while looking for manual processes that can be replaced with digital alternatives. For the sake of terminology clarification, robotic process automation (RPA) and business process automation (BPA) are technologies one can use in enterprise automation. BPA focuses on streamlining complete processes and workflows across the organization, while RPA is responsible for automating individual tasks. UiPath, a prominent RPA vendor, enterprise robotic process automation (RPA) as a software technology that makes it easy to build, deploy, and manage software robots that emulate human actions when interacting with digital systems. Software robots can do things like figuring out what’s on the screen, completing the right keystrokes, navigating systems, identifying and extracting data, and performing a wide range of defined actions. business process automation (BPA) as the automation of complex business processes and functions beyond conventional data manipulation and record-keeping activities, usually through the use of advanced technologies. BPA focuses on “run the business” as opposed to “count the business” types of automation efforts and often deals with event-driven, mission-critical, core processes. Here is what these concepts mean: defines Gartner defines Intelligent enterprise automation enhances the traditional RPA’s capabilities with innovative , such as natural language processing (NLP), and . artificial intelligence (AI)-based technologies computer vision Intelligent enterprise automation can use one or a combination of these technologies to offer complex, innovative solutions. COVID-19 accelerates enterprise workflow management efforts Deloitte and McKinsey, both reputable consultancy firms, conducted surveys that proved the pandemic forced companies to rethink the way they work. McKinsey research shows that the percentage of respondents taking action on automation has increased from 57% in 2018 to 66% in 2020. Source: McKinsey & Company During the same period, Deloitte 441 executives from 29 countries to find that 73% of the respondents had already deployed automation technologies, such as machine learning and robotics. This number is up from 58% in 2019. Enterprise automation will continue its steady rise throughout the following decade. For example, according to Statista, the global robotic process automation market is predicted to surpass . questioned $13 billion by 2030 Source: Statista Enterprise workflow automation benefits In one of its enterprise process automation projects, ITRex helped digital networking and booking services company to build a healthcare RPA solution. This product (EMRs) of the company’s clients. Before deploying enterprise automation solutions, doctors wasted valuable time entering their availability data into various EMRs to give patients an accurate overview. This caused errors and frustration. To resolve this, the client employed ITRex to develop an automation healthcare system that would synchronize the client’s booking service with eClinicalWorks (eCW), one of the most popular EMR solutions in the US. Even though this automation effort was limited in scope, it already brought the following benefits: synchronizes patient appointment data between the company’s booking service and the electronic medical record systems Making the client’s booking service consistent with the eCW without modifying its internal code Eliminating human error Freeing up doctors’ time to take over more appointments instead of wasting time on data entry Reducing costs, as the client didn’t need to hire specialized eCW developers, who are relatively expensive. Neither did they pay eCW API fees Off-the-shelf enterprise automation software vs. custom enterprise automation Off-the-shelf (ready-made, packaged, etc.) software is a commercially offered and licensed digital product that you can deploy at your company for a monthly or annual fee. In contrast, custom solutions are designed and built catering to the requirements of a specific client. It is worth mentioning that some ready-made solution vendors are open to working with clients and customizing their offerings to fit into the client’s system. Below are the main differences between the two options. Disclaimer: this comparison is applicable in many cases. However, there can be exceptions, especially when speaking of customizing off-the-shelf solutions. Off-the-shelf enterprise automation tools are more suited for: Enterprises operating in heavily-regulated industries. In this case, packaged software might already come compliant so that you don’t have to investigate and apply these regulations yourself. Large companies. If large businesses want to implement enterprise-wide automation, it is best to turn to off-the-shelf solutions. Custom enterprise workflow management software would be too expensive, time consuming, and might not cover all the variable use cases. Ready-made products, on the other hand, are designed for this type of client. Additionally, vendors receive user feedback and improve their systems accordingly. Note: if you are a large enterprise that wants to automate only distinct tasks and use cases, feel free to turn to custom software solutions. Business cases with no special requirements where a standard set of features is sufficient. Turning to an to build a custom enterprise automation software is worth considering under the following conditions: RPA consultant Projects with limited automation scope, when three to five use cases are considered Business cases that are unique and complex, where off-the-shelf products would need customization Legacy systems are involved Enterprises with rigid processes that can’t be adapted Getting started with enterprise workflow automation: tips and challenges Vitali advises companies considering RPA or enterprise intelligent automation to prepare for this process across three pillars — governance, data and technology, and the human pillar. Companies can do this alone or together with their selected automation vendor. Governance: Identify the problems your company is trying to solve. For example, a bank may realize 50% of their clients who submitted a personal loan application form end up withdrawing before a decision is made Outline use cases for enterprise automation and prioritize them. We can investigate the business problem mentioned above to discover concrete use cases. Here is one way to proceed. Why do 50% of our clients withdraw? Because they must wait for a prolonged period. Why is that? One reason is that our loan application review process requires approval from five people. Human approval is not something we can automate, so we keep searching further. Another reason is that loan officers need to access data from different systems to make a decision, and afterwards, they enter all the information in the bank’s system. Here is a viable use case — i.e., automating data collection and information input processes. Optimize business processes before automating. Make sure the process is as efficient as possible before you automate. In the loan application example, do we need the approval of five people? Maybe in some cases, three approvals are enough. Define clear business goals you want to achieve with enterprise automation. Coming back to the bank example, the goal is to spend less time processing loan applications and give an answer to the client before they withdraw their file and submit it to competitors. Highlight KPIs to measure the value of automation to the business. One example of the bank’s KPI can be making a decision on personal loan applications within one working day. Ensure executive leadership support. This will help you get other employees to cooperate even when the initiative causes inconveniences or fails to produce value immediately. Identify all the stakeholders involved in enterprise automation. These people can come from different departments and vary in their background and expertise. It is best to make sure their views on automation are aligned. Define risks. Here are some examples: (1) decreased loyalty among employees as they start experiencing job security fears (2) integration with legacy systems can take much longer than we anticipated originally, (3) this new automated system might open vulnerabilities from the security standpoint. Data and technology: Choose the right technology for every business problem. If your company is small, the automation scope is modest, and the use cases are standard, then opt for a small-scale enterprise automation system that covers your needs. Nothing more. Leverage multiple technology solutions to bring end-to-end automation. In theory, it would be nice to have one platform across different departments. But if your business is fragmented, this will not be a viable option. Suppose you have one autonomous isolated (no Internet connection) department with a few straightforward requirements. In that case, a simple custom Python script might suffice, even if your other departments are using more complicated automation software. Select solutions that integrate well with the existing ecosystem. Your ecosystem has its established workflow, make sure the automation tool you choose is compatible with it and can integrate with your applications. Don’t trap yourself with a novel technology that doesn’t fit with your existing tech stack. Pay attention to data quality. Make sure the data you input and generate with this new enterprise automation solution is compliant with your overall data strategy. Humans and change management: Ensure everyone understands automation goals. The new system will take over repetitive, dull tasks and allow employees to focus on what matters and devote more time to creative and strategic duties. Drive workforce transformation, not replacement, if possible. Automation is expected to eliminate as well as create new job opportunities. Research shows workforce automation can displace in the coming years, but it is expected to create 97 million instead. Given this situation, it may be a wiser choice to reskill your employees. 85 million jobs Invest in employee education. Train users on the new work environment and support them to facilitate adoption. Develop an HR strategy to retain employees and attract talent for critical roles. When a part of their everyday duties becomes automated, employees might feel there is no place for them in your company anymore. But this workforce has other key skills that the enterprise can’t afford to lose. This is where the HR department comes in. They need to find ways to keep these people motivated and interested in staying or quickly recruit a replacement if they insist on moving on. Establish an agile way of working. Employees need to be prepared to pivot within their job role, take other responsibilities, and be prepared to learn. 5 Enterprise automation challenges to consider and ways to address them Vitali highlights five main challenges that can cause setbacks in enterprise workload automation initiatives: Struggling to scale: even though in automation, be it process discovery tools or software vendors, scaling is still hindered as a comprehensive automation strategy is lacking. According to Deloitte, only that are implementing and scaling automation have an enterprise-wide automation strategy. As a result, firms automate individual processes in one department but struggle to scale them across the enterprise due to employee resistance or other factors. To address this challenge, you can enlist the C-suite’s support from the start and establish a center for excellence, which would set standards for scaling. enterprises invest heavily 38% of companies Regulations and enterprise-related constraints: if you automate a task that is tied to rapidly evolving regulations, they can soon change, rendering your new solution unusable. Some workflows can’t be automated due to constraints. For example, tasks that require manual approval or processes that need to access data protected with captcha or other tools requiring human interference. Lack of alignment between IT and business functions: this challenge occurs when the IT team has their own goals that are not compatible with those of the business department. They can even be contradicting at times. Both parties can’t understand each other. Businesses want everything to work without appreciating the technical complexity. This creates friction between teams and delays the process. To ensure that everyone is on the same page, you can encourage open and consistent communication, constructive feedback, and collaboration between departments, and remind employees that they are working towards a common goal. Cultural adoption: this is one of the main challenges. While technology-related concerns can be resolved given sufficient time and finances, it is hard to make people adopt a tool when they are not motivated. If you look at enterprise automation as a way to support rather than replace your human capital, making this clear will relieve people from their fears. You may need to prepare and implement a cultural shift. Explain to your workforce which of their responsibilities will be automated and how this will impact their job. Organize training and support people during the learning process. Note that some enterprise automation tools are not user-friendly, which makes them harder to operate and prolongs learning time. Security risks: when you automate tasks, you introduce a new IT system, which in turn will present vulnerabilities and open entrance points for criminals to explore. Also, integration with existing systems will form loopholes for potential security breaches. To minimize these risks, perform security evaluations and risk management and consider the results as an important factor when making the final decision. For a more elaborate list of RPA pitfalls, you can refer to our article on the . top 13 RPA challenges Ready to take action? If after reading this article, you find yourself a perfect candidate for off-the-shelf enterprise automation tools, then go ahead and purchase one. It will be cheaper and faster than building a custom application. But if you want something unique and tailored to your processes and operations, then it’s a good idea to start searching for a vendor providing custom enterprise automation services. Be sure your vendor is familiar with your industry’s regulations and that he is willing to offer continuous support, help you scale, and introduce new features. The ITRex team will not only cover the points mentioned above but can also look beyond the traditional RPA into intelligent enterprise automation thanks to our expertise in AI and other related technologies. Are you looking for a custom enterprise automation solution that fits into your system? Together, you can build something really unique. Drop ITRex consultants a line!

How to Get Started With Enterprise Automation: Tips From ITRex

Joseph Flaherty , Director of Content & Community In the startup world there are two dominant exit strategies: Build and sell your company for millions, or, Build your company and take it public for billions. These are the liquidity events that give the impression that startups are a great way to “get rich quick,” even though building a saleable company often takes the better part of a decade. Less often discussed, or championed, is a third option — the “get rich slow” method of building a company and making millions of dollars in profits, for years or decades. In the first option, a sale, the founders earn enough money to set their family up for generations, in an instant. But there is the possibility for regret, recently given voice by , who walked away from $850M in earnout potential because he didn’t agree with the way his creation was being monetized. WhatsApp co-founder Brian Acton In the second scenario, an initial public offering, immense financial gains are paired with the ability to continue leading your company, subject only to the pressures of the stock market. There’s an added bonus of prestige for joining the elite ranks of public company CEOs. But as Elon Musk has recently learned, no amount of money or esteem will allow you to escape the eye of regulators. The third choice, running a company at scale in perpetuity, is harder to pull off. Basecamp has been proselytizing for the approach to startups for over a decade, urging founders to create companies that are more like than internet monopolists. This summer saw a mini-wave of smaller startups, like and , buying out their early investors, essentially purchasing the freedom to go their own way. Often this class of startup is dismissed as “lifestyle businesses.” That’s a mistake. Italian restaurants Buffer Wistia There are companies that serve as a proofs of concept that this approach to building a startup can scale and rival even public companies. Epic Systems, makers of the leading Electronic Health Record system, records approximately and employs 9,000. Mathworks, creators of the science software standby MatLab earned , and most recently, has a nine-figure run rate and no plans to go public. Atlassian operated this way for years before deciding to go public. MailChimp which announced , up from . $2.5B a year in revenue $900M in revenue EclinicalWorks $600M in revenue run rate $400M in 2016 To put this in perspective, . bootstrapped a company that is 50% larger than one of the hottest SaaS startups of the last decade. In Atlanta. With a founder who studied industrial design in college and taught himself web design. Hubspot had $375M in 2017 revenue MailChimp The founders of these companies pay themselves well. They face no artificial timetables. And they’re free to run their companies the way they want, whether that’s for company meetings, or engaging in unusual marketing approaches, a MailChimp specialty. dressing up as a wizard Before becoming a meme via their infamous ad, they marketed like cereal manufacturers, rewarding fans with , , and . Their imagination was constrained more by physics than budget, as from MailChimp Director of Brand Marketing Mark DiCristina illustrates: Serial coloring books animal-theme beanies pepperoni-scented vinyl toys this anecdote “There was a time when a couple people were joking around and showed Ben an eBay listing for a tractor trailer, along with three Honda race cars, and suggested we turn them into a giant Transformers robot. Ben actually cleared the budget for it, and then he was crushed when he realized it was just a joke.” It’s hard to imagine such a stunt being looked on favorably by a board or public company analysts. While the freedom is fun, there are downsides to this approach: VC provides leverage that no other form of funding can match. Though it’s much derided by bootstrapping zealots, almost every startup of consequence has taken capital at some point in its journey. Venture capital can be a superpower. Founders no longer have the carrot of a potential six or seven figure payday to tempt talent. This kind of company needs to be more thoughtful about things like profit-sharing. Recruiting and retaining talent can be tougher. Even if you don’t plan to list on public markets, there are points at which the government will require financial reporting on par with what’s expected in financial markets. This gives competitors an insight into your business without the benefit of being able to access public capital markets. All successful startups are subject to reporting. The benefit of a sale or IPO is the opportunity to take financial risk off the table. If you sell a company and the market shifts, the gains have been realized, whereas running the company long-term creates financial risk. This can be mitigated by taking a higher salary, or profits in the form of bonuses, but it exposes the team to more variability. The market might change rapidly. It seems like MailChimp’s founders have navigated or mitigated those risks and are choosing to act like mid-century captains of industry — staying loyal to their customers and employees, serving as stewards of their community, and putting off an immediate payday for a chance at building a legacy closer to home. It’s an admirable approach and worth studying. The point of this blog post isn’t to convince you not to raise money. Founder Collective is a VC firm that wants to back companies that will sell or go public in a ten-year time period. But there is a lot to be gained by being thoughtful about the decision when to raise capital and how much. There’s , but plenty of examples of startups dying due to to capital. By limiting funds raised, . So before reflexively deciding to raise more money, or jumping at inbound interest from investors, think a bit about what made these companies work and decide how valuable optionality is to you. no evidence that raising more money leads to better outcomes toxic overexposure $100M exits become pretty darn attractive _VC is a common denominator of the most successful tech startups, but it isn’t a prerequisite, especially at the early…_hackernoon.com 50 Big Companies that Started with Little or No Money

The “Get Rich Slow” Exit Strategy

50 Big Companies that Started with Little or No Money

50 grandes empresas que comenzaron con poco o ningún dinero

20 Best Social Media Management Tools for Small Businesses

A couple of weeks ago, we had a great time hosting the workshop you can see below with Vlad Mihalcea. It was loads of fun and I hope to do this again soon! In this workshop we focused on Spring Boot performance but most importantly on Hibernate performance, which is a common issue in production environments. It’s especially hard to track since issues related to data are often hard to perceive when debugging locally. When we have “real world” data at scale, they suddenly balloon and become major issues. I’ll start this post by recapping many of the highlights in the talk and conclude by answering some questions we missed. We plan to do a second part of this talk because there were so many things we never got around to covering! https://www.youtube.com/watch?v=43qd9vLiajA The Problem with show-sql After the brief introduction, we dove right into the problem with . It’s pretty common for developers to enable the setting in the configuration file. By setting this to true, we will see all SQL statements performed by Hibernate printed on the console. This is very helpful for debugging performance issues, as we can see exactly what’s going on in the database. show-sql spring.jpa.show-sql But it doesn’t log the SQL query. It prints it on the console! Why do we Use Loggers? This triggered the question to the audience: why does it matter if we use a logger and not ? System.out Common answers in the chat included: is slow – it has a performance overhead. But so does logging System.out blocking – so are most logging implementations but yes you could use an asynchronous logger System.out No persistence – you can redirect the output of a process to a file The reason is the fine grained control and metadata that loggers provide. Loggers let us filter logs based on log level, packages, etc. They let us attach metadata to a request using tools like MDC, which are absolutely amazing. You can also pipe logs to multiple destinations, output them in ingestible formats such as JSON so they can include proper meta-data when you view all the logs from all the servers (e.g. on Elastic). Show-sql is Just System Output It includes no context. It’s possible it won’t get into your Elastic output and even if it does. You will have no context. It will be impossible to tell if a query was triggered because of request X or Y. Another problem here is the question marks in the SQL. There’s a very limited context to work with. We want to see the variable values, not questions. Adding a Log with Lightrun Lightrun lets you add a new log to a production application without changing the source code. We can just open the Hibernate file “Loader.java” and add a new log to . executeQueryStatement We can fill out the log statements in the dialog that prompts us. Notice we can use curly braces to write Java expressions, e.g. variable names, method calls, etc. These expressions execute in a sandbox which that they will not affect the application state. The sandbox read only state! guarantees guarantees Once we click OK, we can see the log appear in the IDE. Notice that no code changed, but this will act as if you wrote a logger statement in that line. So logs will be integrated with other logs. Notice that we print both the statement and the arguments so the log output will include everything we need. You might be concerned that this weighs too heavily on the CPU and you would be right. Lightrun detects overuse of the CPU and suspends expensive operations temporarily to keep execution time in check. This prevents you from accidentally performing an overly expensive operation. You can see the log was printed with the full content on top but then suspended to prevent CPU overhead. This means you won’t have a performance problem when investigating performance issues… You still get to see the query, and values sent to the database server. Log Piping One of the biggest benefits of logging capability is its ability to integrate with other log statements written in the code. When you look at the log file, the Lightrun added statements will appear “in-order” with the log statements written in code. Lightrun’s As if you wrote the statement, recompiled and uploaded a new version. But this isn’t what you want in all cases. If there are many people working on the source code and you want to investigate an issue, logging might be an issue. You might not want to pollute the main log file with your “debug prints”. This is the case for which we have Log Piping. Log piping lets us determine where we want the log to go. We can choose to pipe logs to the plugin and in such a case, the log won’t appear with the other application logs. This way, a developer can track an issue without polluting the sanctity of the log. Spring Boot Connection Acquisition Ideally, we should establish the relational database connection at the very last moment. You should release it as soon as possible to increase database throughput. In JDBC, the transaction is on auto-commit by default and this doesn’t work well with the JPA transactions in Spring Boot. Unfortunately, we’re at a Chicken and Egg problem. Spring Boot needs to disable auto-commit. In order to do that, it needs a database connection. So it needs to connect to the database just to turn off this flag that should have been off to begin with. This can seriously affect performance and throughput, as some requests might be blocked waiting for a database connection from the pool. If this log is printed, we have a problem in our auto-commit configuration. Once we know that the rest is pretty easy. We need to add these two fields that both disable auto-commit and tell Hibernate that we disabled it. Once those are set, performance should be improved. Query Plan Cache Compiling JPQL to native SQL code takes time. Hibernate caches the results to save CPU time. A cache miss in this case has an enormous impact on performance, as evidenced by the chart below: This can seriously affect the query execution time and the response time of the whole service. Hibernate has a statistics class that collects all of this information. We can use it to detect problematic areas and, in this case, add a snapshot into the class. Snapshots A Snapshot (AKA Non-breaking breakpoint or Capture) is a breakpoint that doesn’t stop the program execution. It includes the stack trace, variable values in every stack frame, etc. It then presents these details to us in a UI very similar to the IDE breakpoint UI. We can traverse the source code by clicking the stack frames and see the variable values. We can add watch entries and most importantly: we can create conditional snapshots (this also applies to logs and metrics). Conditional snapshots let us trigger the snapshot only if a particular condition is met. A common problem is when a bug in a system is experienced by a specific user only. We can use a conditional snapshot to get stack information only for that specific user. Eager Fetch When we look at logs for SQL queries, we can often see that the database fetches a lot more than what we initially asked for. That’s because of the default setting of JPA relations which is EAGER. This is a problem in the specification itself. We can achieve significant performance improvement by explicitly defining the fetch type to LAZY. We can detect these problems by placing a snapshot in the method of . loadFromDatasource() DefaultLoadEventListener In this case, we use a conditional snapshot with the condition: . event.isAssociationFetch() As a result, the snapshot will only trigger when we have an eager association, which is usually a bug. It means we forgot to include the LAZY argument to the annotation. As you can see, this got triggered with a full stack trace and the information about the entity that has such a relation. You can use this approach to detect incorrect lazy fetches as well. Multiple lazy fetches can be worse than a single eager fetch, so we need to be vigilant. Open Session in View Anti-Pattern On the surface, it doesn’t seem like we’re doing anything wrong. We’re just fetching data from the database and returning it to the client. But the transaction context finished when the post controller returned and as a result, we’re fetching from the database all over again. We need to do an additional query as data might be stale. Isolation level might be broken and many bugs other than performance might arise. This creates an N+1 problem of unnecessary queries! We can detect this problem by placing a snapshot on the call and seeing the open session: onInitializeCollection Now that we see the problem is happening we can solve the problem by defining spring.jpa.open-in-view=false It will block you from using this approach. Q&A There were many brilliant questions as part of the session. Here are the answers. Could you please describe a little bit about Lightrun? Lightrun is a developer observability platform. As such, it lets you debug production safely and securely while keeping a tight lid on CPU usage. It includes the following pieces: Client – IDE Plugin/Command Line Management Server Agent – running on your server to enable the capabilities I wrote about it in depth . here Could Lightrun Work Offline? Since you’re debugging production, we assume your server isn’t offline. However, Lightrun can be deployed on-premise, which removes the need for an open to the Internet environment. Wondering about this sample, will this be available for our reference? The code is all . here As the Instrumentation/manipulation happens via a Server, given that I do not host the instrumentation server myself, what kind and what amount of data is being transmitted? Is the data secured or encrypted in any way? The instrumentation happens on your server using the agent. The Lightrun server has no access to your source code or bytecode! Source code or bytecode never goes on the wire at any stage and Lightrun is never exposed to it. All transmissions are secured and encrypted. Certificates are pinned to avoid a man in the middle attack. The Lightrun architecture received multiple rounds of deep security reviews and is running in multiple Fortune 500 companies. Finally, all operations in Lightrun are logged in an administrator log, which means you can track every operation that was performed and have a full post-mortem trail. You can read more about Lightrun security . here As mentioned, these logs are aged out in 1 hr. Is it possible to save those and re-use them for later use rather than creating log entries manually every time? Lightrun actions default to expire after 1 hour to remove any potential unintentional overhead. You can set this number much higher, which is useful for hard to reproduce bugs. Notice that when an action is expired, you can just click it and re-create it. It will appear in red within the IDE and can still be used for reference. Is IntelliJ IDEA the only way to add breakpoints/logging? Or how is debugging with Lightrun done in production? You can use IntelliJ (also PyCharm and WebStorm) as well as VSCode, VSCode.dev and the command line. These connect to production through the Lightrun server. The goal is to make you feel as if you’re debugging a local app while extracting production data. Without the implied risks. Is there any case where eager loading should be configured always for One-to-Many or Many-to-Many or Many-to-One relations? I always configure lazy loading for the above relations. Is it okay? Yes. If you see that you keep fetching the other entity, then eager loading for this case makes sense. Having eagerness as the default makes little sense for most cases. Do we need to restart an application with the javaagent? The agent would run in the background constantly. It’s secure and doesn’t have overhead when it isn’t used. If we are using other instrumentation tools like say AppDynamics or dynatrace …… does this work alongside? This varies based on the tool. Most APMs work fine besides Lightrun because they hook up to different capabilities of the JVM. Does this work with GraalVM? Not at this time since GraalVM doesn’t support the javaagent argument. We’re looking for alternative approaches, but hopefully the GraalVM team will have some solutions. Is it free to use? Yes! Check out lightrun.com/free Does it impact app performance? Yes, but it’s minimal. Under 0.5% when no actions are used, and under 8% with multiple actions. Notice you can tune the amount of overhead in the agent configuration. Does it work for Scala and Kotlin? Yes. How to use it in production without IDE? The IDE will work even for production, since you don’t connect directly to the production servers and don’t have access to them. The IDE connects to the Lightrun management server only. This lets your production servers remain segregated. Having said that, you can still use the command-line interface to get all the features discussed here and much more. Apart from injecting loggers, what other stuff can we do? The snapshot lets you get full stack traces with the values of all the variables in the stack and object instance state. You can also include custom watch expressions as part of the snapshot. Metrics let you add counters (how many times did we reach this line), tictocs (how much time did it take to perform this block), method duration (similar to tictocs but for the whole method) and custom metrics. You can also add conditions to each one of those to narrowly segment the data. How do we hide sensitive properties from beans? Say Credit card number of user? Lightrun supports PII Reduction, which lets you define a mask (e.g. credit card) that would be removed before going into the logs. This lets you block an inadvertent injection into the logs. It also supports blocklists, which let you block a file/class/group from actions. This means a developer won’t be able to place a log or snapshot there. How can we use it for performance testing? I made a tutorial on this . here When working air gapped on prem is required, how do you provide the Server, as a jar or docker…? This is something our team helps you set up. Will it consume much more memory if we run with the Lightrun agent? This is minimal. Running the petclinic demo on my Mac with no agent produces this in the system monitor: With the agent, we have this: At these scales, a difference of 17mb is practically within the margin of error. It’s unclear what overhead the agent has, if at all. Finally This has been so much fun and we can’t wait to do it again. Please follow , , and for updates on all of this. Vlad Tom myself There are so many things we didn’t have time to cover that go well beyond slow queries and spring data nuances. We had a really cool demo of piping metrics to Grafana that we’d love to show you next time around. Also Published Here

Spring Boot Performance Workshop with Vlad Mihalcea

Author: Peter Schrammel Almost nobody likes writing unit tests - and if you agree, you may be glad to hear that manually writing all of your tests is becoming a thing of the past. We've developed , an AI tool that automatically creates unit tests for Java code, to make it easier to get the unit tests you need without spending the time it takes to write them. Diffblue Cover Diffblue Cover: is a free IntelliJ plugin that uses the same core technology, and is now available for anyone to use with their open-source Java projects. What does Community Edition do? So how is it actually used? Community Edition Diffblue Cover works like this: First, Diffblue Cover ensures that your code is compiled. This is required because it performs an analysis on the bytecode. Then, it tries to trigger executions of paths through each method that it is going to test, using inputs that are similar to those a developer would choose. On the way, it mocks any dependencies that should be mocked. Finally, it figures out what the useful assertions may be and adds them to the test. Note that the assertions always reflect the current behavior of the code; Diffblue Cover is not able to anticipate your intentions and 'fix' the code for you. Diffblue Cover is intended to be used for unit regression testing. Essentially, this means it creates unit tests that reflect the current behavior of your code (and if you'd like more information about that, we have an explanation here). If your code is currently working, Diffblue Cover captures this. Later, when you make changes to the code, these tests may fail and show you possibly unintended changes to the code (so-called "regressions"). It can also help you find bugs by review. What this means for developers Diffblue Cover is significantly faster than writing manual tests from scratch. Sometimes it might not succeed in finding a suitable test for your code, in which case it may return a partial test for you to complete. But because Diffblue Cover creates unit tests in bulk in , it helps you speed up unit test writing for new features. a tiny fraction of the time it'd take to write them Currently, Diffblue Cover is only available for Java, but will be expanded to work with other languages in the future. Generated unit tests that look like they were written by a person The tests that Diffblue Cover creates largely follow the arrange-act-assert pattern: Arrange inputs and mocks Act: run method under test Assert effects Here's an example that Cover created: @MockBean
  private AmazonS3Client amazonS3Client;
  @Test
  public testDownloadFileFromBucket() throws UnsupportedEncodingException {
     StringInputStream objectContent = StringInputStream( );
     S3Object s3Object = S3Object();
     s3Object.setObjectContent(objectContent);
     when( .amazonS3Client
        .getObject(or(isA( .class), isNull()), or(isA( .class), isNull())))
        .thenReturn(s3Object);
     S3Object actualS3Object = .cloudStorageService.downloadFileFromBucket( , )
     assertSame(s3Object, actualS3Object);
  } void new "Lorem ipsum dolor sit amet." new this String String this "bucket-name" "key" Installation and first steps You can download the plugin , or by going to Preferences > Plugins > Marketplace in your IntelliJ IDE, searching for “Diffblue Cover,” and installing the community edition. here To give you an idea of what the tool does and illustrate its features, let’s look at a simple example project that uses the Spring framework: Spring Pet-Clinic. We have forked this project into . You’ll find the branches for each lesson of this tutorial so that you can follow along on your own. https://github.com/Diffblue-benchmarks/Spring-petclinic Your first steps after having installed the plugin are: git clone https://github.com/Diffblue-benchmarks/Spring-petclinic cd Spring-petclinic git checkout a-test-intro Open project in IntelliJ Navigate to the CloudStorageService class This class implements a simple service for uploading to and downloading files from an S3 bucket. @Service
public {

  @Autowired
  private AmazonS3 s3client;

  public PutObjectResult uploadFileToBucket( bucketName, key, File file) { s3client.putObject(bucketName, key, file);
  }

  public S3Object downloadFileFromBucket( bucketName, key) { s3client.getObject(bucketName, key);
  } class CloudStorageService String String return String String return To create tests for this class, right-click on CloudStorageService > Write tests When you open the event log, you'll see what the tool is doing. First, it ensures that the project compiles and figures out for which methods we want to produce unit tests. To create the tests, it has to load the Spring context and find suitable inputs to the methods to exercise paths through these methods. Once the first test has been created you can navigate to the created test source file to see the tests. Further tests will drop in as they are produced. Let’s have a look at this test. The tested service would communicate with an actual S3 bucket. We don’t want this to happen in a unit test, so we mock the S3 client using Mockito. We have to set up the object returned by getObject appropriately, including the content of the file. @ExtendWith(SpringExtension.class)
public {
  @MockBean
  private AmazonS3Client amazonS3Client;

  @Autowired
  private CloudStorageService cloudStorageService;

  @Test
  public testDownloadFileFromBucket() throws UnsupportedEncodingException {
     StringInputStream objectContent = StringInputStream( );
     S3Object s3Object = S3Object();
     s3Object.setObjectContent(objectContent);
     when( .amazonS3Client
        .getObject(or(isA( .class), isNull()), or(isA( .class), isNull())))
        .thenReturn(s3Object);
     assertSame(s3Object, .cloudStorageService.downloadFileFromBucket( , ));
  } class CloudStorageServiceTest void new "Lorem ipsum dolor sit amet." new this String String this "bucket-name" "key" In this example, you can see how Diffblue Cover: Community Edition creates tests that are actually useful and can even handle more complex scenarios, e.g. mocking. Hopefully this overview gives you an idea of how Community Edition works, but if you have questions or need any help, you can contact us through the . Community Forum

How to Start Using Diffblue Cover: Community Edition For Unit Testing

According to Wikipedia, is a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or the frequency and duration of function calls. Software profiling Most commonly, profiling information serves to aid program optimization. Profiling is achieved by instrumenting either the program source code or its binary executable form using a tool called a profiler (or code profiler). One of the most popular profilers in the Java world is . It is a visual tool that integrates command line JDK tools and lightweight profiling capabilities. The project is Open Source and maintained by Oracle, you can find the codebase . The tool was designed for development and production time use. VisualVM here VisualVM was included in the JDK until version 8. Some of its main features: Display Local And Remote Java Processes Display Process Configuration And Environment Monitor Process Performance And Memory Visualize Process Threads Profile Performance And Memory Usage Take And Display Thread Dumps Take And Browse Heap Dumps Analyze Core Dumps Analyze Applications Offline You could find more information about the different features in the project’s webpage, but definitely I would suggest you to just download it and start playing around, it’s “easy” to use. And then there’s , I mean, everybody knows and loves it! Seriously, it’s by far the most used and loved Java Runtime and Framework platform, take a look at the . Spring Boot JRebel 2020 Report Recently I needed to profile a Spring Boot app and made some interesting findings that I wanted to share since these are not really obvious. Prepare your app for profiling Something really cool about Spring Boot is , by “default” you can benefit from one single executable JAR with all the app classes and dependencies in it. One JAR, one App, just execute it and that’s it! FAT JARs FAT JARs are definitely powerful, but there are some tradeoffs when you use them. For example . when creating Docker images And… Explode your FAT JAR. This is fundamental, I wasted a lot of time before on a Windows machine with JDK 8 trying to profile an unexploded JAR (it failed silently). When you need to profile an application using VisualVM! On my current computer, a Mac with JDK 12, the profiler fails to start! (ERROR: ). It’s clear, the classes cannot be found therefore cannot be instrumented. Profiler engine warning: class *FAKE_CLASS_1* that should be instrumented is not loaded by target VM I’ll demo my point using… The ! The best Spring demo project ever! Spring Petclinic Demo App Clone the repo, build the app and explode the JAR file in a new folder: git https://github.com/spring-projects/spring-petclinic.git spring-petclinic
mvn package
mkdir jar-content jar-content/
jar xvf ../target/spring-petclinic-2.4.0.BUILD-SNAPSHOT.jar clone cd cd At the end of the process, you should end up with the following folders: BOOT-INF: Contains all classes and dependencies META-INF: Contains all JAR metadataorg: Contains Spring Boot launcher classes It’s of special interest the file , there you’d find what are your main and start classes. With all that info you’re ready to execute/start your app: META-INF/MANIFEST.MF java -cp .:BOOT-INF/lib/*:BOOT-INF/classes org.springframework.boot.loader.JarLauncher org.springframework.samples.petclinic.PetClinicApplication NOTE: If you’re using Windows, remember to change by and slashes by backslashes. “:” “;” There you go, that’s all we need for now! Profile your app In order to profile your app, and execute it. You should see your app configured under the Local menu. In case you’re trying to profile a remote app keep in mind the download VisualVM following configurations Double click on your app, go to the profile tab and change the profile class to match your Spring Boot app root package! Important: add to the end (to include all classes in that package). For example: “.**” org.springframework.samples.petclinic.** One last final tip: from my experience the best view is the Hot Spots, it allows you to quickly see where are your potential bottlenecks. Final words Software profiling is definitively very useful when trying to understand bottlenecks and potential areas of improvement. A must to know tool for understanding your application and tuning it. Tools like VisualVM really empower you and are super useful to have in your toolbox. Especially useful, the Open Source nature of the tool, you’d find tons of related information out there! And finally, but not least, yes, you can profile a Spring Boot App! In later articles I might write about heap and stack dumps, and see how you can even use Spring Boot Actuators for getting that information. Also published at https://medium.com/kayvan-kaseb/tips-and-tricks-for-profiling-your-spring-boot-app-using-visualvm-de627cae02d1

Tips For Profiling Your Spring Boot Application Using VisualVM

Blockchain has a straightforward concept. All records stored in the blockchain and not saved on a single central storage unit. Multiple computers are running in the network called nodes and having a copy of all the blockchain data. Therefore, when something is updated on the blockchain, all network nodes are informed about it at once. "Blockchain technology is set to change the way healthcare is managed forever. Blockchain allows clinicians and patients alike to be confident that the medical records are accurate and up-to-date as the distributed ledger guarantees an incorruptible, trustless version of the data that can be depended upon a time. An indisputable single version of the truth is not achievable with today's current systems and infrastructure." This is what we mean by decentralization. There is no longer a single source responsible for all data. Okay, that sounds good, but what are the challenges and how the blockchain can solve them? Challenge #1: Accuracy of Medicines and Health Records In today's healthcare sector, all records are stored in central data stores via excel tables. The situation is the same in the health sector, carried out by both state and private companies. Therefore, it is effortless to quickly change this data because someone who can access central data stores can change this data efficiently. Likewise, all the information about a newly invented drug is stored in the central warehouses on computers. The fact that these central repositories become unusable causes all formulas and information to disappear immediately. But thanks to the blockchain, thanks to thousands of nodes working in different parts of the world, all this information is stored in a hackable, unchangeable, and unalterable way. In this way, health and medicine information is protected with maximum security, unlike central data systems. Challenge #2: Data Analytics is Time-Consuming and Resource-Heavy Pharmaceutical companies need to deal with so many health and pharma sources; it is clear that there is a problem with data collection, processing, and ultimately with analytics. For beginners, some essential data may fall from cracks during the first phase, diluting insights from analytics. As if this isn't bad enough, harmonizing data from different sources can be quite time-consuming. Moreover, the long analytical process may not find insights that can help pharma. It is clear, however, that the entire data processing process for pharmaceutical companies should change. After all, managing big datasets is a tough job for both small and large pharmaceutical companies. Challenge #3: Central storages are expensive to use Central storage systems have many expenses, like Rent expenses, electricity expenses, inventory expenses, employee expenses, and many more hidden expenses. Also, these expenses are not for one time only; they must be covered continuously. The same reason lies behind the fact that central data stores can be easily manipulated, because people use it, controlled, and changed. However, decentralized data stores are not under human control, and they do not need a workforce to work. Thanks to the blockchain and its smart contracts, the entire system operates automatically and is also transparent. Featured projects and solutions developed in the blockchain sector FLETA According to the : Blockchain startup Sendsquare (FLETA) has been selected by the government to develop a proof-of-concept project for the nation, which has around , the company announced on Friday. Coindesk report 3.6 million people with diabetes The startup will team with clinical experts and practitioners from Seoul's KyungHee University Medical Center to analyze nine years' worth of diabetes clinical data previously collected by the center. in ordering and storing such a large amount of data will ultimately lead to efficiency improvements for healthcare staff, which means they will spend more time with the people who matter: the patients. The use of blockchain South Korea new data-related regulations that will be effective in December. Once the regulations are applied, more corporations are expected to look to blockchain's benefits for data management and storage. passed States' desires to use blockchain technology and their efforts to achieve this are great. If the South Korea government accomplishes this, this could be a significant development for the healthcare industry around the world, so that more and more government and hospitals in the world can safely store user and pharma data on the blockchain. In the light of these developments, South Korea, can the pathfinder. CHAINLINK "The Chainlink network provides reliable tamper-proof inputs and outputs for complex smart contracts on any blockchain." Decentralized applications often require external data existing outside the blockchain to execute successfully, for example, financial market data for decentralized finance (DeFi) applications. LINK is providing external data to smart contracts securely and reliably to match the underlying blockchain's security properties is a technical challenge, often called "the oracle problem." This project is one of the most prestigious projects of the last years in terms of blockchain infrastructure architect. It performs as a price increase, but it also makes a lot of mention with its agreements and partnerships. Chainlink has a robust infrastructure, and they have a stable place in the ecosystem with its smart contracts technology created over the Ethereum network. Its customers include Google, Binance, and including many more world giants. Chainlink, one of the first projects that come to mind when it comes to smart contracts, wants to contribute to the created for use in the health sector. health sector by building the smart contracts of blockchains Medicalchain uses blockchain technology to create a user-focused electronic health record whilst maintaining a single accurate version of the user's data. Medicalchain Medicalchain enables the user to give healthcare professionals access to their health data. Medicalchain then records interactions with this data in an auditable, transparent, and secure way on . Medicalchain's distributed ledger The application called Myclinic.com utilizes Medicalchain technology to provide immediate retrieval of health records, thereby allowing patients to communicate directly with the doctors and share their health records for online consultations. Giving a patient direct and regular access to their healthcare record and their service provision empowers patients to receive the best possible care. The project also has some reliable partners like Blockchain Research Institue, Blockchain Policy Initiative, etc. CONCLUSION Especially with the DeFi FOMO, blockchain and cryptocurrencies have gained an essential place in the economic system. But the blockchain makes the most of technological opportunities and the broader ecosystem of uses cases waiting for us. Health, which is one of the most critical sectors in the world, is part of this. While the use of financial instruments is growing at an incredible rate, it is more important than ever to apply blockchain technology to the health sector and change and make the entire system related to health data more robust. (Disclaimer: The Author is associated with FLETA)

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