Have you been bitten by unexpected costs in the cloud? Whether you are all in with serverless, cloud-native services, on demand and reserved instances, or you build systems and applications with all those things, it is very likely you have had a bad experience with unexpected costs. Why is that? Let me ask you, what is your DevOps tool for observing cost?

Whether you’re the consumer or producer of an API, you’ve no doubt seen that good error handling can make debugging easier. And you may have noticed that error handling works best when everyone speaks the same language and has the same expectations. But what makes for good error handling? And how can we implement it and ensure consistency across our application?

Picture this: you’re standing in the largest meeting room in your company. Behind you, a huge LED monitor. In front of you, all members of the C-suite. The CTO, your direct boss, is visibly nervous. The CEO looks interested and somewhat excited. The CFO looks happier than usual, though it probably has more to do with his very successful golf round the day before and nothing to do with the presentation you’re about to give.

Here are a few updates you can look forward to in LogDNA’s log management and analysis features.

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.

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.

A customer of ours reported a limit on number of packets in Amazon’s EC2 instances. According to the report, it didn’t happen on all instance types, and didn’t happen all the time. Also, it was unrelated entirely to bandwidth or MTU. According to the report, packet transmission rates were limited the same as CPU on t2/t3 instances — each instance earns credits which, when exhausted, cause throttling.

This is the second part of a series on the CloudReady dashboards and visualizations. The first part covered basics like Overviews, Refresh, and Layout settings. In this second part, we’ll cover more advanced creation and usage of dashboards. In part 3 and 4 we’ll cover actual widgets and how they can be used.