A decade ago, DevOps teams were slow, lumbering behemoths with little automation and lots of manual review processes. As explained in the 2020 State of DevOps Report, new software releases were rare but required all hands on deck. Now, DevOps teams embrace Agile workflows and automation. They release often, with relatively few changes. High-quality DevOps change management is no longer a nice-to-have, it’s a must. For a lot of DevOps teams, this is easier said than done.

Chaos Engineering is one of the hottest new approaches in DevOps. Netflix first pioneered it back in 2008, and since then it’s been adopted by thousands of companies, from the biggest names in tech to small software companies. In our age of highly distributed cloud-based systems, Chaos Engineering promotes resilient system architectures by applying scientific principles. In this article, I’ll explain exactly what Chaos Engineering is and how you can make it work for your team.

Every Java developer should follow coding standards and best practices to develop secure Java code. It is critical your code is not vulnerable to exploits or malicious attacks. In recent times, even big organizations like eBay, the CIA, and the IRS have fallen victim to vulnerabilities in their applications that have been discovered and exploited by attackers. The following guidelines provide a solid foundation for writing secure Java code and applications.

The Internet of Things (IoT) has quickly become a huge part of how people live, communicate and do business. All kinds of everyday things make up this network – fridges, kettles, light switches – you name it. If it’s connected to WiFi, it’s part of the Internet of Things. IoT raises significant challenges that could stand in your way of fully realizing its potential benefits.

System traceability is one of the three pillars of observability stack. The basic concept of observability is of operations, which include logging, tracing, and displaying metrics. Tracing is intuitively useful. Identify specific points in an application, proxy, framework, library, runtime, middleware, and anything else in the path of a request that represents the following of either ‘forks’ in execution flow and/or a hop or a fan out across network or process boundaries.

Coralogix can be configured to automatically and dynamically archive logs to an S3 bucket. This saves Coralogix customers money, but of course there are times when the data needs to be reindexed. This operation counts the reindexed logs against the daily quota. Many times customers would like to search and focus on the exact logs to be reindexed or even query the logs outside of Coralogix all together.

Elastic is “an index”, “a search engine”, “a big data solution”, an analytics platform with advanced data visualizations and incredibly fast search capabilities. In short, it’s a solution for many problems. The Elasticsearch platform provides a distributed search cluster that enables large amounts of data to be indexed and searched at scale.

In a previous post, we went through a few input plugins like the file input plugin, the TCP/UDP input plugins, etc for collecting data using Logstash. In this post, we will see a few more useful input plugins like the HTTP, HTTP poller, dead letter queue, twitter input plugins, and see how these input plugins work.