Operations | Monitoring | ITSM | DevOps | Cloud

Today, we’re adding to the groundwork we’ve established to provide enterprise organizations with a modern approach to data unification to improve insights. Our True North unifies all the many layers of data into a single stream to provide better insights so you can make better decisions and adjustments and bring value to the organization.

Nowadays businesses are confronted with increasingly sophisticated cyber threats that pose significant risks to their operations, data, and reputation. To combat these threats effectively, organizations often turn to Managed Security Service Providers (MSSPs) for expert guidance and support. Unlike traditional Managed Service Providers (MSPs), MSSPs specialize in delivering comprehensive security and network monitoring solutions tailored to the unique needs of their clients.

CUDOS is one of the six specialized dashboards, in the AWS Cloud Intelligence Dashboards framework. The Cloud Intelligence Dashboards framework is focused on providing comprehensive usage and cost insights for AWS resources. It is a very crucial tool that provides deep insights that can be used to optimize AWS infrastructure.

I have always had a special fondness for Postgres, particularly captivated by its JSONB capabilities, which is at the core of what I love as it stands as a testament to its adaptability. This functionality exemplifies Postgres’s ability to adapt to modern apps’ rapidly changing needs to support structured and unstructured data to coexist seamlessly within the same database environment. The capabilities of PostgreSQL are not limited to its ability to manage relational and non-relational data.

Mohammed Al Sahaf serves as Technical Product Manager at Samsung Electronics Saudi Arabia. Outside his day job, he serves with the Caddy team to tackle the web of problems facing web servers in the third millennium. Mohammed is the author of Kadeessh, formerly caddy-ssh, and the maintainer of numerous Caddy modules. When he isn’t programming, he is trying to catch up on life and sleep with the help of coffee.

Sift is a machine-learning-powered diagnostic feature in Grafana Cloud that SREs and DevOps teams can use to automate routine parts of incident investigation, such as searching for new errors in logs, surfacing recent deployments, or identifying overloaded Kubernetes nodes. We want Sift to springboard you into an investigation, so useful context is already there by the time you see an alert or declare an incident.