As organizations have expanded their application portfolios into diverse cloud environments, teams have gradually acquired separate tools to monitor different dimensions of performance. But when monitoring tools are adopted piecemeal—one for application performance, another for security vulnerabilities, still another for network performance and so on—the lack of a unified observability platform inevitably makes life challenging for the engineers who support these environments as a whole.
Observability tool sprawl represents a growing concern, and not just for large enterprises. Even midsized organizations are running into this problem as they move their core workloads to the public cloud, typically to multiple cloud vendor platforms. According to TechTarget’s Enterprise Strategy Group, 85% of organizations reported using at least six different observability tools1—and monitoring with such an assortment tends to be even more burdensome in a multi-cloud environment. Overall, the legacy approach to monitoring amounts to major operational and cost inefficiencies for organizations, many of which are simultaneously struggling to gain adequate visibility into their infrastructure and applications.
The benefits of an integrated platform approach to observability
Fortunately, cloud service providers today—often in concert with independent software vendors operating within their ecosystems—have come to market with a more efficient, flexible and resilient approach to cloud observability, replacing the fragmented visibility made possible through many separate tools.
The observability solutions that embrace this new approach seamlessly stitch together monitoring, security, performance management, tracing and more. And they provide these functions not through separate dashboards but via a comprehensive, intelligent and contextual view of activity across infrastructure and applications, system-wide. This type of unified observability platform replaces the patchwork quilt of legacy tools that teams naturally accumulate over time.
Today, working with a one-stop shop for cloud observability is not only desirable but essential. The ability to avoid the costs, complexity and confusion of observability tool sprawl allows organizations to get a single view of the truth for everything from application and infrastructure performance to data anomalies and security risks—all in an accurate and timely fashion. Additionally, the integration of AI operations (AIOps) adds workflow automation and much-needed intelligence to the process, alleviating much of the management burden that has traditionally fallen to overworked and understaffed engineers.
Taking a unified approach to observability with Datadog and Google Cloud
Datadog is an experienced provider of enterprise-wide observability solutions for all leading cloud platforms, including Google Cloud. Datadog’s long relationship with Google provides a unified observability capability in cloud-only, hybrid cloud and multi-cloud environments.
Datadog is optimized to take Google Cloud’s many native observability capabilities to an even higher level, offering a reliable, resilient, integrated and cost-efficient approach to observability. With Google Cloud often at the heart of an organization’s cloud modernization journey, Datadog’s collaboration with Google Cloud enables end-to-end observability.
In providing insight into both known and unknown behavior, Datadog allows organizations to gain a comprehensive view across applications, infrastructure, networks, services and functions, including those essential to support DevOps and cybersecurity.
For Google Cloud customers that are just starting their cloud migration journey or are already well established in the cloud, Datadog is an important partner. Whether an organization’s workload is a Google Kubernetes Engine container, a Google Anthos on-prem environment or some hybrid configuration, Datadog makes migration planning flexible and efficient.
Its ability to seamlessly integrate with Google Cloud services allows organizations to take full advantage of many Google Cloud resources, including Autopilot, to reduce system overhead and enhance system-wide performance. It also provides features enabling anomaly detection, outlier detection, forecasting and more, drawing upon vast telemetry data captured from across the entire application stack and infrastructure. Best of all, all this valuable data is consolidated, integrated, unified and visualized for organizations in a single pane of glass.
For more information about Datadog observability solutions for Google Cloud, please visit here.
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1 “Observability and Demystifying AIOps,” TechTarget’s Enterprise Strategy Group, 2023
