Operations | Monitoring | ITSM | DevOps | Cloud

Databricks is a critical part of many organizations’ tech stacks, facilitating analytics, machine learning, and other leading-edge data engineering tasks. But when a service like Databricks becomes essential, it also tends to become a cost black hole, leading engineering teams to a quandary: How can you keep Databricks costs in check without hurting application performance? At CloudZero, we give organizations unparalleled visibility into their Databricks costs.

Zoom has an interesting concept they call a “minimum version enforcement policy.” The video conferencing platform enforces a Quarterly Lifecycle Policy, meaning that every three months, specifically in February, May, August, and November, Zoom updates the minimum required versions of its apps and SDKs. All users, system admins, and developers must be on at least the specified version to continue using the platform. Why?

Getting the right information at the right time can dramatically change the direction of your business. Yet, you may not have enough time to keep up with everything. We get it. So, our team pulled a few all-nighters (so you don’t have to), and we bring you the key SaaS statistics every SaaS leader, team, and engineer should see right now. You can dig even deeper by checking out the sources we included.

DevOps has become the backbone of modern software delivery. By breaking down the silos between development (dev) and operations (ops), DevOps teams can move faster, deploy more frequently, and maintain more reliable systems. But with this need for speed comes the necessity of visibility. And this is where DevOps dashboards impress. In this guide, we’ll cover the essentials of DevOps dashboards.

In 2018, I dashed off a punchy little blog post in which I observed that teams with good observability seemed to spend around ~20-30% of their infra bill to get it. I also noted this was based on absolutely no data, only my own experiences and a bunch of anecdotes, heavily weighted towards startups and the mid-market tech sector. This post should have ridden off into the sunset years ago. To my horror, I have seen it referenced more in the past year than in all preceding years combined.

Amazon Web Services (AWS) is still the largest cloud service provider today. With over 240 cloud products, this Amazon.com subsidiary offers cloud, on-premises, serverless, and edge computing services. But bigger isn’t always better, and we’ll share why, plus explore the top AWS alternatives to consider if you’re thinking about making a switch.

Imagine navigating a cross-country road trip using nothing but a paper map from the 1980s. Sure, you might eventually reach your destination, but you’d likely miss faster routes, real-time traffic updates, and helpful insights along the way. That’s what it can feel like for modern finance teams to rely solely on spreadsheets for complex financial modeling.

Amazon EventBridge is a powerful tool for building event-driven architectures. It’s built to connect and simplify real-time data processing and automation across your cloud stack (AWS services, customs apps, and SaaS applications). But when it comes to pricing, things can get a little tricky. Estimating EventBridge costs at scale is often daunting. There are just too many moving parts involved. That’s why in this guide, we’re breaking down what goes into an Amazon EventBridge bill.

If you provide services such as live streaming, social media networking, and analytics, you need a robust platform to speed up your read/write operations per second. Caching reduces latency by storing frequently accessed objects in faster memory (RAM or in-memory data stores instead of slower disk-based storage). Amazon ElastiCache is a managed, in-memory data store and caching service in one.

Companies running Kubernetes workloads often discover significant and unexpected waste or underutilized resources in their compute environment. Smart organizations implement a host of FinOps activities to mitigate this waste and the cost it incurs: … and the list goes on. But these are infrastructure-level optimizations that don’t address waste within an application.