Operations | Monitoring | ITSM | DevOps | Cloud

As businesses increasingly transition to cloud-based services, the demand for data center resources has surged, leading to higher electricity consumption. Currently, data centers contribute to about 3% of global carbon emissions and account for roughly 1-1.5% of global electricity demand. As a result, the need for sustainable solutions in cloud computing has never been more urgent.

Over the last few years, Google Cloud has grown at the fastest rate of any cloud service provider today. From 2020 to 2021, Google Cloud’s IaaS offering, GCP, grew 64%, followed by Microsoft Azure (51%) and Alibaba Cloud (42%), according to Gartner. Yet Google Cloud isn’t flawless. Here’s what we mean and some of the top Google Cloud alternatives you’ll want to consider today.

Prometheus is a widely adopted open-source monitoring and alerting toolkit, popular among DevOps and SRE teams for its robust metrics collection and powerful query language (PromQL). It is fast, reliable, and purpose-built for modern, cloud-native environments. However, Prometheus may not suit all teams or projects. In 2025, several alternatives offer different strengths that might better match your specific monitoring needs.

Java applications run on top of the JVM — a powerful but complex runtime environment that re-implements many OS features. It has its own memory management, garbage collector, and dynamic code compiler (JIT). While these features help with performance and portability, they often make troubleshooting a real challenge. At Coroot, we recently improved our support for continuous profiling in JVM-based applications.

Exploitation of vulnerabilities increased 180% year over year from 2023 to 2024, which means that quickly and effectively securing endpoints – always a priority – will only continue to escalate. Patching these vulnerabilities promptly, but without sacrificing stability, can present operational challenges. One way to achieve this: ring deployment — a technique that progressively scales rollouts to user groups.

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.

A year ago, we set out to transform log analytics pricing by making it as flexible, transparent, and as customer-friendly as possible. We built a model that aligns cost with business value, charging only for data storage and analytics executed. With Flex Licensing, customers can scale usage up or down without breaking the bank, eliminating hidden costs and inefficient licensing structures. There is no more pre-planning or tiering of log data; there is just log ingest with sensible pricing.

Have you ever launched a website, made a DNS change, and then waited and waited some more for it to go live? You are not alone.

Most cloud infrastructure and deployment misconfigurations start innocently enough: a dev under pressure to ship quickly tweaks a configuration file or adjusts a permission setting to make something work. It's not malicious and it might even be well thought out, but these small changes can cause a cascade of reactions that bring down production in seconds.

Every organization has two non-negotiables: stay compliant and stay online. But achieving both—especially at scale—isn’t easy. Many IT teams still rely on manual processes for backups, documentation, and recovery. And when something goes wrong? The cost isn’t just measured in downtime, but in regulatory penalties, lost trust, and business disruption. What if network compliance wasn’t a separate process—but could naturally integrate into your recovery strategy?