Cloud Monitoring is a tool that provides automated out-of-the-box dashboards to collect metrics to Google Cloud Services. Cloud Monitoring also allows monitoring of multi-cloud and hybrid cloud environments.
Events, metrics, and metadata are presented using a rich query language that aids in identifying issues and uncovering patterns. Service-level goals measure the user experience and enhance the collaboration between developers and users.
One service integrated for metrics, monitoring uptime dashboards, alerts, and metrics helps reduce time spent searching between different systems. In addition, observing in context makes metrics available on Google Cloud page resources.
Applications Manager’s support for Google Compute Engine (GCE), Google’s infrastructure-as-a-service (IaaS) virtual machine offering, helps shed light on resource utilization at the individual host level by tracking instance, firewall, and quota metrics.
Google Cloud Platform
Google Cloud Platform is a public cloud service that hosts a wide range of services such as compute, storage, big data, machine learning (ML), application development, and more. Like any other cloud-powered application, Google Cloud requires constant monitoring to keep its overall health and performance intact.
Google Cloud Monitoring
The monitoring of Google Cloud means gaining visibility into the performance, availability, and health of your applications and your infrastructure.
Google Cloud monitoring covers the following features.
- Monitor system metrics that are automatically collected through Google Cloud services.
- Allow the SRE best practices widely utilized extensively by Google, SLOs, and SLIs.
- Get application metrics from the workloads on GKE by using the managed metrics collection pipeline.
- Utilize your Ops Agent to collect application metrics and the deep-system metrics of Virtual Machines.
- Create custom dashboards and alerts that work with tools for managing incidents.
Key features of Google Cloud Monitoring
Google Cloud Console integration
Find and track every one of the Google Cloud resources and services without additional configuration, and is integrated into Google Cloud console. Google Cloud console.
Monitoring of SLO
Automatically determine or custom creates Service-level goals (SLOs) for specific applications. You can also set alerts when violations of SLOs occur.
Custom Metrics
Use your application to track business-level and application-specific metrics through Cloud Monitoring.
Ops Agent
Install the Ops Agent onto Your Google Cloud Virtual Machines to gather detailed data and logs from both your system and applications. Use the console’s step-by-step tutorial to learn how to install the agent on the live VM.
Logging integration
Do a drill-down from chart and dashboards to log. Then, create visualizations, alerts, and visualizations on metrics based on log information.
Multiple projects and support for group/cluster
Create metrics scopes for monitoring one or more projects. Then, resource groups define relations based on resource names tags, security groups, regions, projects accounts, regions, and other factors. Finally, use these relationships to create customized dashboards and topology-aware alarming policies.
Alerting
Create rules that alert you whenever events occur or when a specific custom or system-specific metric violates your set rules. You can define multiple conditions for intricate alerting policies. Notify users via Slack, email, SMS, PagerDuty, and more.
Monitoring of uptime
Verify whether you have access to your Internet-connected URLs, APIs, VMs, and load balancers using probes all over the world with checking uptime. Create alerts so that you are immediately notified of an interruption.
Google Cloud Monitoring Prices
| FEATURE | PRICE | FREE ALLOTMENT PER MONTH | EFFECTIVE DATE |
|---|---|---|---|
| Monitoring data | $0.2580/MiB: 150-100,000 MiB
$0.1510/MiB: 100,000-250,000 MiB $0.0610/MiB: >250,000 MiB |
The entire set of Google Cloud metrics 2
One first-time 150 MB per bill account to the chargeable metrics |
July 1, 2018 |
| Monitoring data that has been ingested through GKE workload metrics | $0.15/million samples 3 1: the first 1-50 billion samples
$0.12/million samples: next 50-250 billion samples $0.09/million samples: >250 billion samples |
Non-applicable | February 1, 2022 |
| Monitoring API calls | $0.01/1,000 API-related calls (Write API calls are for free) | The first 1,000,000 API calls are included in the billing account | July 1, 2018 |
Monitor CPU and memory details
We can observe it from the Google Cloud console with data provided by the hypervisor for CPU usage. But before you can install a monitoring agent, first, you must activate google-monitoring-enable and google-logging-enable metadata on your Virtual Machine instance to enable the agent to collect the data.
In GCE, the virtual hardware resources like memory size, CPU count, etc. Accessible to a specific virtual machine are divided and assigned to various workloads.
Long periods of CPU usage could indicate a performance bottleneck. Therefore, make sure that you allocate enough nodes to ensure that CPU utilization is lower than the recommended limit.
Establishing benchmarks and monitoring the utilization of your CPU compute instances using the GCP monitoring tool will assist in provisioning you compute resources promptly.
Achieve maximum network efficiency
To get the highest possible egress rate, you can send the traffic through an internal IP associated with a different Google Cloud VM in the same zone as the sending VM within the same VPC network or VPC network connected to VPC Network Peering.
Selecting the best kind of instance will assist you in optimizing the speed of your network’s throughput. In addition, application Manager’s Google cloud performance monitoring features, you can monitor the Google cloud platforms, monitor the performance of your network and applications hosted on your instance, and receive notifications whenever unexpected decreases in throughput occur.
GCE has the limitation of 2 Gbits/second on each core CPU. Therefore, to avoid network saturation, increase the capacity by upgrading the instance to a bigger instance.
The maximum egress possible is determined by the machine type of the sending VM. For example, if you select the larger N2, N2D, or C2 kinds of machines, you could reach as high as 100 Gbps the TIER-1 bandwidth throughput.
Track quota metrics with ease
GCE sets limitations on the number of resources that a project may consume. In addition, the application Manager’s Google cloud platform integration tool permits users to monitor quota limits to track the consumption of resources in time, prevent unexpected surges in utilization, and anticipate and address potential issues before the end-users are affected.
Keep tabs on disk utilization.
The long-term duration of heavy use of disks may affect the performance of other applications that are hosted within this same system.
To determine if the root for your program’s performance problems is due to an issue with your disk, be aware of the data you’ve written onto your disk by using the Applications Manager Google monitoring program.
Furthermore, increasing the volume of information written to disk will aid in overcoming long periods of I/O requests that are slow.
Conclusion
Google Cloud Monitoring solution offers automated out-of-the-box metric assemblage dashboards for Google Cloud services. The integrated monitoring service includes metrics, uptime dashboards, alerts, and metrics that help reduce time spent searching between different systems. In addition, the ability to view metrics in context makes them accessible from Google Cloud page resources.
Amit Doshi is a Cloud Engineer who has experienced more than 5 years in AWS, Azure, and Google Cloud. He is an IT professional responsible for designing, implementing, managing, and maintaining cloud computing infrastructure, applications, and services.