Software teams have found themselves in the center of the business’ strategy. Their strategic decisions on technologies to invest in has resulted in greater agility and the ability to build products that differentiate their companies in the market. As a result, optimizing the ability for software teams to deliver by investing in stronger tooling has become a core priority.
Speedscale was built primarily to provide engineering teams with better insight into their applications over time, replaying single transactions for root cause analysis that give developers and SREs confidence that tomorrow’s application code will work just as well in production as it did yesterday.
As the world of technology continues to progress, so are the technologies that developers work with on the daily. Whether it’s cloud native, Kubernetes, serverless, or distributed architectures, every developer team has encountered the difficulties of working with them. Even more so, they’ve felt the challenges associated with trying to find the solutions to those same difficulties. But what if it was as easy as opening a book?
Testing in production simply means testing new code changes in production, with live traffic, in order to test the system’s reliability, resiliency, and stability. It helps teams solve bugs and other issues faster, as well as effectively analyze the performance of newly released changes. Its overall purpose is to expose problems that can’t be identified in non-production environments for reasons that may include not being able to mimic the concurrency, load, or user behavior.
Kubernetes is one of the current leading technologies. Its adoption has seen tremendous growth in the past few years. The concept of containers is a paradigm that appears to be the predominant medium of software development and deployment in the coming future. Containers help maintain consistency across various platforms, as they pack an application with its dependencies to help move it from one platform to another.
Large portions of software development budgets are dedicated for testing code. A new component may take weeks to thoroughly test, and even then mistakes happen. If you consider software defects as security issues then the concern goes well beyond an application temporarily crashing. Although even minor bugs can cost companies a lot of time to locate the bug, resolve it, retest it in lower environments, then deploy it back to production.
Cloudera Data Engineering is a serverless service for Cloudera Data Platform (CDP) that allows you to submit jobs to auto-scaling virtual clusters. CDE enables you to spend more time on your applications, and less time on infrastructure. CDE allows you to create, manage, and schedule Apache Spark jobs without the overhead of creating and maintaining Spark clusters.
Last month, we were proud to launch our Hitachi Kubernetes Service, a true storage-as-a-service (SaaS) offering to improve the performance and management of multiple Kubernetes environments. By enabling users to manage their clusters simply and securely across any major cloud provider and on premises, Kubernetes can play an instrumental role in businesses’ modernization efforts. It’s for this reason that we are always working to get it on the radar of our existing clients.
As we see more customers adopting Rookout for debugging cloud-native applications, we are not surprised to learn that a significant number of them work in a microservice environment. In the most common case among these customers, each service has its own code repository maintained by the team who develops the service.
