Advances in generative AI are rapidly transforming the IT operations landscape. According to Enterprise Strategy Group, 85% of organizations use or plan to deploy AI across many functional areas, including ITOps. AIOps platforms can apply advanced GenAI to quickly identify an incident’s root cause, impact, and recommend steps to resolution. When fed the correct information, AIOps gives IT teams immediate access to context-rich insights.

Tech providers often provide valuable resources to help you optimize your network. Here are ten of our recent favorites. Cloud, network, data center, and managed service providers often go beyond just offering their services. Explore any of your providers’ websites, and you’ll often find an abundance of resources with actionable guidance that can help improve and maintain an efficient enterprise network.

If you’re a developer, you may well be familiar with the scenario. You’re writing code and you want to test your changes against a copy of the production database. One that’s representative of the size and distribution characteristics and retains referential integrity so that, when your changes are released, they won’t result in a failed deployment that will take hours to resolve. But there’s a problem. The database copy you’re working with isn’t up to the job.

We’re excited to announce that as part of our expanded alliance with Sumo Logic, observIQ extended its support for Sumo’s platform. This allows customers to send logs and metrics to Sumo Logic, leveraging our telemetry pipeline, BindPlane. We’ve also made it possible to automatically recommend processors in our pipeline that format data specifically as Sumo Logic expects—once Sumo Logic is a destination for BindPlane.

Open source software refers to computer programs with source code available for anyone to inspect, modify, and distribute. Unlike proprietary software, open source software is developed collaboratively by a community of developers. One of the main benefits of open source software is cost savings. Because the source code is freely available, organizations can use and customize the software without paying licensing fees, reducing costs, especially for large-scale deployments.

Whether you’re running a service mesh composed of HAProxy instances or facilitating communication between multiple systems, ensuring the authentication of traffic between your services is critical. This zero-trust security model operates under the assumption that you should not extend trust without verification, even within your own systems. By verifying every interaction, you mitigate the risks that arise when third parties imitate your systems.

There’s a major outage. Support tickets are mounting. Everybody from engineering to legal is scrambling for information. You have more Teams notifications clamouring for attention than you do minutes to address them, and it’s hard to know where to begin. What comes next is a balancing act—mitigating the impact, updating colleagues, managing action items, or updating a status page that will be seen by millions.

Fact: No one likes traffic congestion. That’s why no one pines for the days before Google Maps. Thanks to navigation apps on our phones and cars, we can see traffic updates that help us avoid busy roads during rush hour and reach our destinations faster. The same logic applies to content delivered over the Internet. Congestion on the web happens when data packets flood the network, causing delays and packet loss.

Many SaaS companies struggle to get engineers to take charge of costs and lower cloud expenses. Confused business leaders often put the problem on the shoulders of the engineers: Surely, it’s just that the engineers don’t care enough to stay within budget, or maybe they just don’t want to participate in the culture of cost efficiency leadership is trying to build. But what if your engineers actually do want to optimize costs—they just don’t have the tools and data to do so?

Gartner predicts that by the end of 2025, 80% of organizations will use cloud automation tools to orchestrate workloads. The firm also forecasts that spending on public cloud services will hit $679 billion by the end of 2024, with SaaS leading the cloud computing market. This surge in cloud spending will shape the future of SaaS, and cloud automation tools will play a key role in this transformation.