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Services

The Services dashboard centralizes all of your running services, allowing you to quickly detect if and when issues occur. You can use the dashboard to investigate the different services, operations, and logs inside each one.

Services

Services overview

You can choose how you want to view your services: a table view or a map view. Switch between the views by clicking on the buttons at the top right corner of the screen.

Table view

The table view contains the following details:

  • Name of each service
  • Impact level - Determines the severity of each event, calculated based on the latency and request rate
  • The Environment in which this service is located
  • Request rate - Number of requests per second, in numeral and graph view
  • Latency - The duration it takes data to travel in the environment, presented in milliseconds and graph view
  • Error ratio - Both percentage and graph view

At the top of the chart, you can adjust the view to match your monitoring needs.

You can compare your view to a previous time frame and view the differences in the graphs and trends.

service compare

Change the time frame to range from 2 hours to 2 days ago.

service time

Choose which environments and operations you want to display in the chart.

service filters

Or, if you're looking for a specific service, use the search to see all the matching results.

service search

Clicking on the Clear filters will remove all of the filters.

Map view

The map lets you visualize your system architecture, understand the connections between elements, and focus on your services and operations.

The filters change the time frame, service, environment, and operations. You can choose to view the data according to the following:

  • Request rate - Number of requests per second, in numeral and graph view
  • Latency - The duration it takes data to travel in the environment, presented in milliseconds and graph view
  • Error ratio - Both percentage and graph view

You can also zoom in and out of the map, move the elements around, and click on them to get additional info in graph form. Clicking on the button will take you to the service overview screen.

service map overview

Dive deeper into your services

Clicking on one of the services opens a new page with additional info, including a visual representation of the service’s current error ratio, request rate, latency, and a breakdown of the service’s operations, infrastructure, and logs. Each data point is compared to the time frame of your choice (last day or last week), helping you understand the trends and know which area you should focus on.

At the top of the page, you can change the time frame, choose which nodes or pods to focus on, or manually update the data by clicking the refresh icon.

service deeper

Hovering over the graphs provides additional info for the time point you've chosen:

  • The Request rate graph shows the number of requests made per minute
  • The Latency graph provides a milliseconds count of how long it takes for data to travel in your environment
  • The Errors graph analyzes the percentage of errors that occurred
  • The HTTP status code graph measures the distribution of various HTTP status codes

graphs

Operations overview

This table includes all of the operations running inside the chosen service with this additional data:

  • Operation name
  • The operation’s Impact level, calculated based on the latency and request rate
  • Request rate - Number of requests per second, in numeral and graph view
  • Latency - The duration it takes data to travel in the environment, presented in milliseconds and graph view
  • Error ratio - Both percentage and graph view

Use the search bar to find a specific operation or the arrows at the bottom of the table to navigate the operations.

operations view

(Single) Operation overview

Click on an operation's name for a more in-depth view of its current state. You get a graph overview of the operation's request rate, latency, error ratio, and HTTP status code.

You can also view the operation's spans with these additional details:

  • Time
  • Trace group
  • Trace ID
  • The Operation related to this span
  • Duration
  • Status code

Clicking on any span will direct you to its trace view, helping you pinpoint where failures occur and find the leading contributors to slow transaction performance.

operation spans view

Infrastructure overview

View the CPU and memory consumption inside the service. The graphs represent a breakdown of consumption by the hour.

Hovering over the graphs provides values for the specific time point, allowing you to see how much CPU was used by the deployment at this specific time or how much memory this deployment used.

hovering graph

You can toggle your view between pods and nodes inside the service.

Track Deployment Data

You can enrich your Service Overview graphs by indicating recent deployments, helping you determine if a deployment has increased response times for end-users, altered your application's memory/CPU footprint, or introduced any other performance-related changes.

To enable deployment tracking ability, run the Telemetry Collector on your Kubernetes clusters. You can also activate this process manually by installing Logz.io Kubernetes events Helm chart and sending Kubernetes deploy events logs.

Once enabled, navigate to Services and choose one of your running services. The deployment marker will appear in your graphs, marked by a vertical line.

deployment popup

You can view additional deployment data by clicking on the line. This data includes the deployment time, the associated service and environment, and a quick link to view the commit in your logs.

Click Go to commit to access and view your own code related to this deployment, allowing you to probe deeper into the relevant data.

Important

To activate the Go to Commit button, go to your app or service and add the following annotation to the metadata of each resource's versioning you want to track: logzio/commit_url: "", and the URL structure should be: "https://github.com/<account>/<repository>/commit/<commit-hash>". Learn more.

Detect Anomalies

Logz.io's Anomaly Detector helps you engage a predictive approach towards your data. It monitors your service latency and error ratio to detect any abnormal patterns or data points that deviate from the expected behavior, helping to detect and address issues, improve security, and ensure system reliability.

To get started with the Anomaly Detector, you'll need to set up the anomaly you want to track.

In List view, select the service you wish to monitor, click the three dots, then choose Edit Anomaly Detector. In Map view, click on the operation you want to monitor and select Edit Anomaly Detector.

anomaly detector

The Anomaly Detector automatically selects the service, and you can choose to monitor all operations, which will aggregate the anomalies by service, or select up to five specific operations from which to aggregate anomalies.

Next, you can determine the sensitivity of the anomaly detector. Low triggers an alert after finding 3 deviations in the data, Medium triggers when 2 deviations are detected, and High triggers immediately as the first deviation is detected.

Finally, you can choose if and how to receive notifications whenever new anomalies are detected.

Click Save to create the anomaly detector.

anomaly popup

Once your anomaly detector is up and running, you'll see an indicator in the list and map view next to each service and operation being monitored.

no anomaly