So much of our world has moved away from the slow and methodical, towards the agile and iterative. In transport, for example, everything is “on demand”, constantly changing and adaptable. The same is true for developers. With movements and philosophies such as CI/CD, everything is about moving quickly, yet smartly. Test automation is an integral part of this development philosophy.
In the past, applications would be deployed by installation on a host, using the operating system package manager. This was a heavy solution with tremendous reliance on the operating system package manager and increased complexity with libraries, configuration, executables and so on all interconnected. Then came containers. Containers are small and fast, and are isolated from each other and from the host.
From production monitoring to security concerns, it’s critical for businesses to analyze and review their log data. This is particularly true for large and enterprise companies, where the sheer amount of data makes log analysis the most efficient way to track key indicators. CTOs, in particular, are dealing with the challenges of this massive amount of data flowing through their organization, including how to harness it, gather insights from it, and secure it.
The way we think about development started with Waterfall – sequential, solid, conservative – moved to Agile, whose origins can be traced back to a somewhat romantic story at a ski resort in Utah, and is now heavily influenced by DevOps.
With the increasing adoption of containerization, the need arose to manage, schedule and control clusters of containers, and that’s where Kubernetes comes in. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications, generally being Docker containers. When interfacing with Kubernetes, 2 competing tools are often discussed: Terraform, and Helm.
The amount of data being generated today is unprecedented. In fact, more data has been created in the last 2 years, than in the entire history of the human race. With such volume, it’s crucial for companies to be able to harness their data in order to further their business goals. A big part of this is analyzing data and seeing trends, and this is where solutions such as Graphite and Grafana become critical.
Production logs can help ensure application security, reveal business insights and find and understand errors, crashes, and exceptions. But as useful as logs are, they’re difficult to manage and hard to keep track of. Making matters worse is that as log data volume grows, so does the difficult task of maintaining and managing them. It’s for this reason that developers, DevOps engineers, and CTOs turn to log management tools.
Organizations both small and large that deal with personal data must be compliant with GDPR rules. At Coralogix, we’ve been working hard to be prepared for GDPR. Preparing your data for GDPR can be a daunting task, so we thought we’d shed some light on the issue.
Describing your profession to other people is never easy, especially if you work in the development field. Non-technical people often lack the understanding and terms that may seem just so obvious to you. And if you’re a DevOps expert, multiply the struggle times 10. To help, we’ve put together a cheat sheet style post to explain DevOps to non-technical people.
