Imagine the following scenario: you’re running a small corporate website, and suddenly, your service becomes unreachable, throwing a 503 (service unavailable) http error at your customers and website visitors. The irritated messages start flooding in to support. Worried, you walk through the usual administrative checks, to make sure it’s not what you think it is. Is the webhost up?
Boston and Tel Aviv, October 24, 2018 — Logz.io, the leader in AI-powered log analysis, releases the first robust security application built on the open source ELK Stack, bringing powerful and scalable security monitoring and analysis directly into the DevOps workflow.
Facing the growing threat of cybercrime, and to answer compliance requirements, more and more organizations are looking at their DevOps and Operations teams to implement security. The term “security”, however, often triggers negative feelings among engineers. The reason for this is that security is associated with siloed, sequential and complicated processes — all roadblocks to fast development and deployment.
We founded Logz.io four years ago with a vision to provide a platform for engineers like us to operate the next generation of applications and infrastructure. As engineers, we experienced firsthand the challenges of running large-scale, open-source tools and the frustration of dealing with slow, proprietary tools which were not designed to support the rapidly changing technology stack we operated.
While there are plenty of articles aiming to instruct newbies on “how to become a DevOps engineer”, none of them answer a simple question – should you become one to start with? For me, it’s been a long and winding journey to becoming what is called a Site Reliability Engineer (SRE). The journey was unplanned, and for each step, I had to figure out what I want my next challenge to be and how to achieve it.
In Elasticsearch parlance, a document is serialized JSON data. In a typical ELK setup, when you ship a log or metric, it is typically sent along to Logstash which groks, mutates, and otherwise handles the data, as defined by the Logstash configuration. The resulting JSON is indexed in Elasticsearch.
Most software and systems generate audit logs. They are a means to examine what activities have occurred on the system and are typically used for diagnostic performance and error correction. System Administrators, network engineers, developers, and help desk personnel all use this data to aid them in their jobs and maintain system stability. Audit logs have also taken on new importance for cybersecurity and are often the basis of forensic analysis, security analysis, and criminal prosecution.
In many projects, the product development workflow has three main concerns: building, testing, and deployment. Each change to the code means something could accidentally go wrong, so in order to prevent this from happening developers adopt many strategies to diminish incidents and bugs. Jenkins, and other continuous integration tools (CI) are used together with a source version software (such as GIT) to test and quickly evaluate the updated code.
Welcome to autumn! Here in New England we anxiously await the transition to winter as our leaves start to change color and the summer heat begins to temper. It’s been a busy few seasons for us – we’ve introduced new features and launched our new community efforts. Want to learn more? Read on!
