The cloud is limitless – a key factor in its appeal – but it also introduces a new set of problems. Enterprises are looking to innovate at rapid speed, to achieve business outcomes, and deliver superior user experiences. But the majority of enterprises need to continue to maintain complex hybrid infrastructures as well as diversify their cloud strategies across multi-cloud environments.

Today’s DevOps teams can reach project goals quickly because they rely on continuous integration and continuous development (CI/CD) tools that automate tasks. The problem is that there are tons of CI/CD tools out there. How do you know which one serves your team’s needs best? Jenkins stood out as a top contender for years after its release in 2011. More recently (2018), Jenkins X appeared as an alternative.

Big data experts already agree that the amount of generated data is growing exponentially and forecast that it will reach 175 zettabytes by 2025. That projection is predicated upon current realities, which include a growing number of internet users and the billions of embedded systems and connected devices around the world. Even conceptualizing that amount of data is daunting — but then consider how best to manipulate and export it.

Cisco ACI is an enterprise-class, software-defined networking (SDN) solution that provides complete control of the data center network. Using a policy-based approach, Cisco ACI delivers security, performance, and scalability for today’s demanding applications. Cisco ACI is part of the broader Cisco SDN portfolio, which also includes Nexus switches and Application Centric Infrastructure (ACI) controllers. If you are looking for a way to improve your data center network, Cisco ACI may be the answer.

Distributed tracing is an essential process in the modern world of cloud-based applications. Tracing tracks and observes each service request an application makes across distributed systems. Developers may find distributed tracing most prevalent in microservice architectures where user requests pass through multiple services before providing the desired results.

Did you know that nearly 15% of IT budgets go towards maintaining legacy systems? Recent data suggests that these systems cost hundreds of millions annually to operate and maintain. For that reason, many companies continue to invest in moving their systems away from expensive on-premises to the cloud, where maintenance is more cost-effective and consistent thanks to modern monitoring capabilities.

The cloud has revolutionized the way businesses operate. It allows organizations to access computing resources and data storage over the internet instead of relying on on-premises servers and infrastructure. While this flexibility is one of the main benefits of using the cloud, it can also create security and compliance challenges for organizations. That’s where cloud governance comes in. Cloud governance is a framework for managing and regulating how data is accessed and used in the cloud.

Managing application performance has evolved –requiring ITOps teams to become more involved in understanding application performance and users of APM solutions. Keeping an eye on what affects business outcomes has expanded outside the infrastructure to include the users dependent on applications. Modern ITOps teams can no longer ignore the application performance, status, user experience, and overall health of the application alongside the supporting infrastructure.

Managing Kubernetes version upgrades can be a formidable undertaking. API versions are graduated, new features are added and existing behaviors are deprecated. Version upgrades may also impact applications needed by the Kubernetes platform; affecting services like pod networking or DNS resolution. At LogicMonitor, we ensure our Kubernetes version upgrades are successful through a process designed to instill collaboration and due diligence in a repeatable fashion.

In the world of DevOps, every second counts. Problems need to be fixed fast, but with the intention that it’s done with a legitimate purpose for when something’s wrong. Continuous monitoring helps with automation and setting up the right kinds of alerts. If the system is going haywire, every moment not acting can make things worse. That’s why intelligent alerting is critical for enabling observability and continuous effective monitoring.