Sumo Logic ahead of the packRead article
Gain deeper insights and improve app performance with GCP monitoring
Correlate performance issues with errors and failures to proactively identify critical Google Cloud Platform (GCP) application problems. Get to the root cause quickly with pattern detection using machine learning.
GCP Monitoring: Secure your apps and keep your users happy
Identify critical GCP application problems proactively by easily correlating performance issues with errors and failures. Get to the root cause quickly with pattern detection using machine learning.
Eliminate blind spots with support for key GCP services and modern architectures. Simple integration with Google Stackdriver and out-of-the-box content provides visibility into Google App Engine, VPC, IAM and Cloud-Audit.
Collect metrics from 35 different Google Cloud services and custom application-specific metrics to identify critical GCP application problems proactively. Get to the root cause faster with AI-powered LogReduce® and LogCompare® pattern analysis.
Identify, correlate and prioritize threats faster and streamline incident investigation with security analytics. Maintain compliance with internal and external standards, including PCI, HIPAA, GDPR, and more.
What is Google Cloud Platform monitoring?
Google Cloud Platform (GCP) monitoring refers to tracking and analyzing the performance, availability, and security of applications, Google Cloud services and infrastructure hosted on the Google Cloud Platform. It involves using monitoring tools and services to collect, analyze, and visualize data on system behavior, resource usage, and user experience and to alert stakeholders when issues arise. GCP monitoring helps organizations ensure that their cloud-based environments perform optimally, identify and resolve issues quickly, and optimize resource usage to improve operational efficiency and cost-effectiveness.
What metrics can you monitor with GCP monitoring?
You can stay on top of a wide range of metrics with GCP monitoring to get insights into the performance, availability and health of your cloud-based resources. Here are some examples of metrics that you can monitor with GCP:
Compute Engine: CPU usage, disk I/O, network traffic, memory usage, and uptime.
Cloud Storage: Read/write requests, latency, and availability.
Cloud SQL: CPU usage, memory usage, disk usage, and database connections.
Kubernetes Engine: CPU and memory usage, pod status, and cluster health.
Load Balancing: Requests per second, error rate, latency, and backend status.
Pub/Sub: Subscription backlog, message delivery rate, and error rate.
Cloud Functions: Function execution time, memory usage, and error rate.
Bigtable: Read/write requests, latency, and availability.
Cloud CDN: Cache hit rate, cache fill rate, and cache evictions.
Cloud Run: Request count, response latency, and CPU usage.
When evaluating a GCP monitoring solution, what capabilities or features should one look for?
When evaluating a GCP monitoring solution, look for:
Ease of use: The monitoring solution should be easy to set up, configure, and use, with intuitive interfaces and streamlined workflows.
Scalability: The solution should be able to handle monitoring for large and complex environments, with the ability to scale up or down as needed.
Real-time monitoring: The solution should provide real-time monitoring and alerting capabilities, allowing you to respond quickly to issues and ensure high availability of your resources.
Customization: The monitoring solution should allow you to customize dashboards, alerts, and reports to meet your specific needs and requirements.
Data collection and analysis: The solution should provide comprehensive data collection and analysis capabilities, with the ability to collect and analyze metrics, logs, traces, and other types of data from various sources.
Integrations: The monitoring solution should integrate seamlessly with other GCP services and third-party tools to provide a holistic view of your environment.
Security: The monitoring solution should have robust security features, including secure data transmission, access controls, and encryption of sensitive data.
Cost-effectiveness: The solution should provide cost-effective pricing models and offer flexible billing options based on your usage and requirements.
Overall, a good GCP monitoring solution should provide comprehensive monitoring capabilities, easy integration, and a user-friendly interface that helps you quickly and easily identify and resolve issues.
What sets Sumo Logic apart from other GCP monitoring tools?
Sumo Logic offers several unique features that set it apart from other similar solutions. Here are some key differentiators:
Advanced machine learning and analytics that leverages advanced machine learning and analytics capabilities to automatically detect and correlate issues across multiple data sources, providing real-time insights and proactive alerts.
Flexible deployment options, including cloud-native, hybrid, and multi-cloud deployment options, allowing organizations to choose the model that best suits their needs.
Seamless integration with other GCP services and third-party tools, providing a single pane of glass for monitoring and troubleshooting.
Real-time data streaming, allowing organizations to collect, analyze, and act on data in real time, ensuring high availability and performance of their resources.
Unified platform that provides end-to-end visibility and insights into the entire application stack, from the infrastructure to the application layer, helping organizations identify and resolve issues faster.
Overall, Sumo Logic offers advanced machine learning and analytics capabilities, flexible deployment options, seamless integration, real-time data streaming, and a unified platform, providing organizations with the insights and tools they need to ensure optimal performance and availability of their cloud-based resources.