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"I don't always test," muses the Most Interesting Man in the World, on one of the most evergreen tech meme posters of all time, "but when I do, I test in production." I have been laughing at that meme ever since someone posted it on the wall at work way back in. 2013? It's hilarious! Since then, "test in prod" has become shorthand for all of the irresponsible ways we interact with production services, or cut corners in our rush to ship.
Almost every time I present RSocket to an audience, there will be someone asking the question: "How does RSocket compare to gRPC?" Today we are going to find out.
By Benoit Rostykus, Gabriel Hartmann Noisy Neighbors We’ve all had noisy neighbors at one point in our life. Whether it’s at a cafe or through a wall of an apartment, it is always disruptive. The need for good manners in shared spaces turns out to be important not just for people, but for your Docker containers too. When you’re running in the cloud your containers are in a shared space; in particular they share the CPU’s memory hierarchy of the host instance.
Dynatrace news. Can you believe it’s been two weeks since our annual Perform Summit Barcelona? If you were unable to attend the event, don’t worry, you can catch up on all the action below. The week in Barcelona far exceeded our attendees’ expectations, with more speakers, more breakout tracks, and more activities! With each session at near capacity, it’s no surprise people are already asking when our next event will be.
PALO ALTO, Calif., June 6, 2019 – ScaleGrid , the Database-as-a-Service (DBaaS) leader in the SQL and NoSQL space, has announced the expansion of their fully managed MySQL Hosting services to support Amazon Web Services (AWS) cloud. The platform allows MySQL AWS administrators to automate their time-consuming database operations in the cloud and improve their performance with high availability, disaster recovery, polyglot persistence, and advanced monitoring and analytics.
Blocking code is code which blocks executing threads until their operations finish. It's not always bad to block a thread and wait until the result is ready but there are situations where it's not optimal from a throughput and memory point of view. This article assumes some basic knowledge about the differences between blocking and non-blocking code.
Who's Hiring? Triplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Make your job search O (1), not O ( n ). Apply here. Need excellent people? Advertise your job here! Fun and Informative Events. Advertise your event here! Cool Products and Services. For heads of IT/Engineering responsible for building an analytics infrastructure , Etleap is an ETL solution for creating perfect data pipelines from day
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Who's Hiring? Triplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Make your job search O (1), not O ( n ). Apply here. Need excellent people? Advertise your job here! Fun and Informative Events. Advertise your event here! Cool Products and Services. For heads of IT/Engineering responsible for building an analytics infrastructure , Etleap is an ETL solution for creating perfect data pipelines from day
Dynatrace news. A lot of time has passed since the Dynatrace UFO was printed, assembled, installed and hooked up with our Dynatrace Delivery Pipelines and Production Monitoring the first time. Since then, we have seen many folks around the world install their own UFOs, visualizing the quality of their delivery pipelines or the problems that Dynatrace Davis detected in their production environments.
A complete guide to contact center or call center testing with tools and techniques: A Contact Center Testing is a type of testing done on Omnichannel customer journeys to thoroughly. Read more Contact Center Testing (Call Center Testing) Guide. The post Contact Center Testing (Call Center Testing) Guide appeared first on Software Testing Help.
It's easy for modern, distributed, high-scale applications to hide database performance and efficiency problems. Optimizing performance of such complex systems at scale requires some skill, but more importantly it requires a sound strategy and good observability, because you can't optimize what you can't measure. This session explains a performance measurement and optimization process anyone can use to deliver results predictably, optimizing customer experience while freeing up compute resources
Amazon and a lot of cloud vendors such as Microsoft and Google have services around machine learning (ML), artificial intelligence (AI), and virtual assistants. A popular one that might come to mind is Amazon Alexa, something I’ve written quite a few tutorials around over the years. The concept around Alexa is simple. Provide the Alexa service some audio, have that audio converted into text or some other format that can be evaluated, execute some code, and respond with something to be spok
Dynatrace news. We’re happy to announce the launch of Dynatrace Synthetic private browser monitors! We continue to grow our public synthetic monitoring locations, but customers using Dynatrace Synthetic still need to monitor the performance and availability of internal web applications. One of the most-requested features has been the ability to run synthetic browser monitors on premise.
According to Garter, artificial intelligence will be omnipresent in all spheres of technology and will successfully make its presence prominent among the top investment priority. The post The Role of Artificial Intelligence in Software Development and Testing appeared first on Kovair Blog.
The Timeout Design Pattern states that you should not wait for a service response for an indefinite amount of time — you should rather throw an exception instead of waiting for too long. This will ensure that you are not stuck in a limbo state while continuing to consume application resources. In my earlier blog post, I discussed the fallacies of Distributed Computing and how service calls made over the network are not reliable and might fail.
Data validation for machine learning Breck et al., SysML’19. Last time out we looked at continuous integration testing of machine learning models , but arguably even more important than the model is the data. Garbage in, garbage out. In this paper we focus on the problem of validation the input data fed to ML pipelines. The importance of this problem is hard to overstate, especially for production pipelines.
Dynatrace news. Docker, Inc. contributed the containerd container runtime to the Cloud Native Computing Foundation (CNCF) in 2017. In 2019, Containerd became the 5th project to reach CNCF’s highest maturity level, graduation. Containerd integrates with the Kubernetes Container Runtime Interface (CRI) and manages the lifecycle of containers on Kubernetes worker nodes.
With so many different metrics available to measure dozens of different aspects of a web page, it can be a struggle to know how best to quantify that page’s overall web performance. In this post, we discuss why there are so many metrics, explore what is “the best” metric, and discuss how you can use the Lighthouse Score to better your own performance.
I'm not a believer in having standards for test coverage. I know teams that require 60%, 70%, or 80% test coverage for their code. I don't like having standards like this because different code has different requirements for testing. Straightforward code like getters and setters don't really need to be tested. However, more complex code that encapsulates business rules should be tested.
WebP has become a popular image format. Therefore, we’ve developed a solution to even better integrate WebP into our service. We’re happy to announce that WebP Caching has landed! The new feature integrates into the existing CDN and is available to all customers. We offer both a one click solution with no change required on your origin server as well as an approach where you can deliver the WebP assets from your origin server.
Dynatrace news. Dynatrace became the de facto standard for monitoring Web-scale software production environments , which also means to present huge numbers of monitored services, processes and hosts. Given a real-time monitoring environment with several thousands of hosts operating a much higher number of running processes and software services. The latest release of Dynatrace dramatically improves the load speed of loading such large lists of services, processes, and hosts.
“‘Tech debt is taking a loan against next month’s income in order to buy a feature today”‘ The rollout of our founder and CEO Mik Kersten’s Flow Framework has led me to a whole new understanding of how software should be built. At first, I wasn’t sure about the idea that there are four (and only four) types of work involved in delivering software, and I spent a lot of time thinking about how to debunk this idea.
While solving issues related to NFRs (especially application performance), I always think about why we as developers give less importance (honorable exceptions are always there) to performance. Is this due to a lack of awareness? Many times, we start thinking of performance only at the time of a performance test or after deployment.
“How fast is a website?” While it’s a simple question on the surface, it can be challenging to answer. In the past, the answer would be based on the load time of a page, but over the years, we have evolved our approach to site speed to incorporate new metrics, alone or in combination with existing metrics. To build fast sites and stay competitive, it is critical for people passionate about performance to stay informed about new metrics and the methodology behind them.
Dynatrace news. Cluster events audit logging. From a compliance perspective, audit traces are an absolute necessity. There are many legal concerns that must be adhered to, and audit logs serve as an official record that can be provided when an auditor asks for proof of compliance. Security is another area in which audit logs can be invaluable. Audit logs are stored at the cluster nodes where system changes are executed.
Last week I attended a panel on ‘ Women leaders in tech: how to arrive, survive and thrive ’, an event that focused on how Vancouver tech companies can attract and retain women in leadership roles. Run by the UBC Computer Science department and sponsored by Tasktop as part of our company’s ongoing commitment to diversity in tech, the evening featured a star-studded roster of women panelists, all of whom are leaders in tech in one form or another: Before the event started, the crowd chatted with
NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight. Financial Analytics – Financial services and financial technology (FinTech) are increasingly turning to automation and artificial intelligence to fuel their decision making processes for investments.
In this article, you will learn about the importance of writing accurate test plans and how an effective test plan can help to prevent errors. The post Why Writing an Accurate Test Plan Can Prevent Errors? appeared first on Kovair Blog.
Dynatrace news. OneAgent. Java. Added support for Java 12. Added support for Spring WebFlux WebClient. Added support for Vert.x 3.6, 3.7. IBM Integration Bus. Improved error handling in IIB message flows by supporting thrown exceptions and TryCatch nodes. General improvements. Added support for all POSIX-compliant user and group names to full-stack OneAgent installer for Linux, thus making it possible to also use dots, underscores, and hyphens.
Continuous integration of machine learning models with ease.ml/ci: towards a rigorous yet practical treatment Renggli et al., SysML’19. Developing machine learning models is no different from developing traditional software, in the sense that it is also a full life cycle involving design, implementation, tuning, testing, and deployment. As machine learning models are used in more task-critical applications and are more tightly integrated with traditional software stacks, it becomes increas
How Often Does Your App Crash? It’s a great question because there are several nuances to it. For one, the question is better phrased as “How often do your users have a poor experience?” This is because true “crashes” (those cases where the app suddenly closes and there is a stack trace for the closure) represent only a small fraction of cases that the user would label as a crash.
One of the more perplexing problems to troubleshoot in SQL Server can be those related to memory grants. Some queries need more memory than others to execute, based on what operations need to be performed (e.g. sort, hash). SQL Server’s optimizer estimates how much memory is needed, and the query must obtain the memory grant in order to start executing.
One of the key decisions we need to make in software architecture and in our organisations is when and where to create shared services and organise teams to build them. Creating a shared dependency can boost the productivity of downstream teams. They can outsource some of their product’s responsibilities to another team owned by another service, and can instead focus more on innovating on their core capabilities.
Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection. Normally, GPU nodes don't have much room for SSDs, which limits the opportunity to train very deep neural networks that need more data. For example, one well-respected vendor's standard solution is limited to 7.5TB of internal storage, and it can only scale to 30TB.
Estimates can be useful when building software. There is the immediate comfort in having expectations, but there are also practical benefits. Estimates allow for the proper prioritization of work. We don’t just work on things that are important, we work on things that give us a good amount of value for the time we have to put into them. Photo by Mike Szczepanski Unfortunately, estimates are often inaccurate.
Everyone who is old enough to remember the sound of connecting to the Internet with a dial-up modem or of AOL announcing that "You've got mail" is acutely aware that there is an upper limit to how fast something can be downloaded, and it never seems to be as fast as we would like it. The availability of bandwidth increases at a staggering rate, but we're never happy.
Towards federated learning at scale: system design Bonawitz et al., SysML 2019. This is a high level paper describing Google’s production system for federated learning. One of the most interesting things to me here is simply to know that Google are working on this, have a first version in production working with tens of millions of devices, and see significant future expansion for the technology (‘ we anticipate uses where the number of devices reaches billions ’).
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