Operations | Monitoring | ITSM | DevOps | Cloud

Modern application deployments rely heavily on containerization for its scalability, availability and ease of maintenance. Legacy applications implemented before the containerization era often use monolithic, hardware-centric architectures that are difficult to scale and manage. These legacy applications may have multiple services bundled into the same deployment unit without a logical grouping.

The first continuous integration (CI) tools were all self-hosted, meaning they ran on a developer’s local computer or server. Although this setup was viewed favorably by dev teams at the time, it has limited flexibility, and developers had to spend time maintaining the infrastructure.

The second quarter is now over and after the start of our V3 at the beginning of this quarter we are super happy to announce that it’s now out in Alpha but there is so much more to speak about so without further due, let me show you all the great things we achieve during the past quarter 🚀

Service level objectives (SLOs) state your team’s goals for maintaining the reliability of your services. Adopting SLOs is an SRE best practice because it can help you ensure that your services perform well and consistently deliver value to users. But to gain the greatest benefit from your SLOs, you need ongoing visibility into how well your services are performing relative to your objectives.

Two years ago today, we shared some insights of 200 CTOs from growing US and EU startups on the topics of the Cloud and their working methodologies (to find out here). Welcome to the second series: “Heroku Dilemma: The Growing Startups' Journey.”

A few weeks ago we had a major incident. We were releasing our Practical Guide to Incident Management, and after posting about it online an incident.io employee noticed that the page wasn’t loading. Just to set the scene, I’ve been at incident.io for 3 months and don’t have any experience of incidents in my previous role. When the team got paged I expected this to be one of those “follow along and learn how the wizards work their magic” exercises.

We have a term we like to use when we meet CFOs who have just gotten their biggest AWS bill ever: bill shock. Bill shock is when finance suddenly rings the alarm that the bill is “too high” and gets everyone scrambling to explain what they’re spending money on. It often happens when the bill reaches a new milestone (the first million, ten million, or hundred million) or growth trajectory (it doubled in a quarter!?). The problem with bill shock is that it can be highly disruptive.

This post is the third in a series of deeper dive articles discussing DORA metrics. In previous articles, we looked at: The third metric we’ll examine, Change Failure Rate, is a lagging indicator that helps teams and organizations understand the quality of software that has been shipped, providing guidance on what the team can do to improve in the future.