Application Monitoring – Golden Signals

Golden signals in application monitoring are a set of key performance indicators (KPIs) that provide a comprehensive view of an application’s health and performance. These signals are crucial for ensuring that an application meets its service level objectives (SLOs) and delivers a satisfactory user experience. Golden signals help teams quickly identify and respond to issues, ultimately improving system reliability and user satisfaction. The four primary golden signals are:

  1. Latency: Latency measures the time it takes for a request to travel from the user’s device to the application and back. It’s a critical metric because users expect applications to respond quickly. High latency can indicate bottlenecks or performance problems within the application, its dependencies, or the network. Monitoring latency helps identify and address performance issues before they impact the user experience.
  2. Error Rate: Error rate measures the percentage of requests that result in errors or failures. This includes HTTP 5xx status codes, database query failures, or any other unexpected errors. A high error rate can indicate issues with application code, infrastructure, or third-party services. Monitoring error rates helps teams identify and fix bugs or infrastructure problems promptly.
  3. Traffic: Traffic refers to the volume of requests or transactions processed by the application. Monitoring traffic helps teams understand how the application’s load varies over time. Sudden spikes in traffic can lead to performance problems or outages if the application isn’t scaled appropriately. Additionally, understanding traffic patterns can inform capacity planning and resource allocation.
  4. Saturation: Saturation measures the resource utilization of the application and its underlying infrastructure. It includes metrics like CPU usage, memory usage, and disk I/O. Monitoring saturation helps teams ensure that the application and its dependencies have enough resources to handle the current load. High saturation levels can lead to performance degradation or outages if resources become exhausted.

Docker: Docker main commands

Docker is a powerful platform for developing, shipping, and running applications inside containers. Here are some of the main Docker commands that you’ll frequently use:

1. Docker Version:

  • Check the installed Docker version.

docker --version

2. Docker Help:

  • Get help and see a list of Docker commands and their descriptions.

docker --help

3. Docker Images:

  • List all locally available Docker images.

docker images

4. Docker Pull:

  • Download a Docker image from a registry (e.g., Docker Hub).

docker pull image_name:tag

5. Docker Run:

  • Create and start a new container from an image.

docker run [options] image_name [command]

6. Docker PS:

  • List running containers.

docker ps

7. Docker PS (All Containers):

  • List all containers, including stopped ones.

docker ps -a

8. Docker Stop:

  • Stop a running container gracefully.

docker stop container_id_or_name

9. Docker Kill:

  • Forcefully stop a running container.

docker kill container_id_or_name

10. Docker Start:

  • Start a stopped container.

docker start container_id_or_name

11. Docker Remove:

  • Remove a stopped container.

docker rm container_id_or_name

12. Docker Logs:

  • View the logs of a container.

docker logs container_id_or_name

13. Docker Exec:

  • Run a command inside a running container.

docker exec [options] container_id_or_name command

14. Docker Network:

  • List and manage Docker networks.

docker network ls

15. Docker Volume:

  • List and manage Docker volumes.

docker volume ls

16. Docker Build:

  • Build a Docker image from a Dockerfile.

docker build -t image_name:tag path_to_Dockerfile_directory

17. Docker Compose:

  • Manage multi-container Docker applications using a Compose file.

docker-compose [options] command

18. Docker Save and Load:

  • Save an image as a tarball and load it from a tarball.

docker save -o image_name.tar image_name:tag docker load -i image_name.tar

19. Docker Push:

  • Push a locally built image to a Docker registry.

docker push image_name:tag

20. Docker Search:

  • Search for Docker images on Docker Hub.

docker search search_term

These are some of the essential Docker commands to get you started. Docker provides many more commands and options for more advanced use cases and customization. You can always refer to the official Docker documentation or use the docker --help command to explore more options and details for each command.

SSH: How to copy my SSH key to a remote host

To copy your SSH key to a remote host, you can use the ssh-copy-id command, which is a convenient way to install your public key on a remote server. Here are the steps to do this:

  1. Generate SSH Key (if you haven’t already): If you don’t have an SSH key pair (public and private keys) already, you can generate one using the ssh-keygen command. Open a terminal on your local machine and run: ssh-keygen -t rsa -b 4096 -C "your_email@example.com" Replace "your_email@example.com" with your actual email address. This command will generate a new SSH key pair and store it in the default location (~/.ssh/id_rsa for the private key and ~/.ssh/id_rsa.pub for the public key).
  2. Copy the Public Key to the Remote Host: Use the ssh-copy-id command to copy your public key to the remote host. Replace your_username and remote_host with the appropriate values:bashCopy codessh-copy-id your_username@remote_host You’ll be prompted to enter your password on the remote host for authentication.Note: If you’re using a custom SSH port, you can specify it with the -p option, like this: ssh-copy-id -p custom_port your_username@remote_host
  3. Authenticate with Your SSH Key: After successfully copying the SSH key to the remote host, you can now log in without entering a password. The SSH key authentication will be used instead.Test this by trying to SSH into the remote host: ssh your_username@remote_host You should be logged in without being prompted for a password.

By following these steps, you’ve securely copied your SSH key to the remote host, allowing you to log in without needing to enter a password each time. This is a more secure and convenient way to access remote servers.

PostgreSQL: How to display block I/O metrics (input/output) on a PostgreSQL server

To display block I/O metrics (input/output) on a PostgreSQL server, you can use various methods and tools. Here are some options:

  1. pg_stat_statements:
    • PostgreSQL’s pg_stat_statements extension can provide insight into the number of blocks read and written by specific queries. To use it, you need to enable the extension and monitor the pg_stat_statements view.
    First, enable the extension by adding or uncommenting the following line in your postgresql.conf file and then restarting PostgreSQL:shared_preload_libraries = 'pg_stat_statements' After that, you can query the pg_stat_statements view to see I/O statistics for specific queries:SELECT query, total_time, rows, shared_blks_read, shared_blks_hit, local_blks_read, local_blks_hit, temp_blks_read, temp_blks_written FROM pg_stat_statements; This query will display I/O metrics for the recorded statements.
  2. pg_stat_activity:
    • You can also use the pg_stat_activity view to monitor ongoing queries and check their I/O activity. This view includes information about the current query being executed, such as the number of blocks read and written.SELECT pid, query, pg_size_pretty(pg_stat_get_blocks_fetched(pid)) AS blocks_fetched, pg_size_pretty(pg_stat_get_blocks_hit(pid)) AS blocks_hit FROM pg_stat_activity; This query shows the process ID (pid), the query being executed (query), the number of blocks fetched, and the number of blocks hit in the shared buffer cache.
  3. pg_stat_bgwriter:
    • The pg_stat_bgwriter view provides statistics about the background writer process, which manages PostgreSQL’s background I/O operations. It includes information about buffers written and other I/O-related metrics.SELECT checkpoints_timed, buffers_heckpoint, buffers_clean, buffers_backend, buffers_alloc FROM pg_stat_bgwriter; This query will show various I/O-related metrics related to background writing.
  4. Operating System Tools:
    • You can also use operating system-level monitoring tools to track I/O metrics for the PostgreSQL process. Common tools include iostat on Linux and Task Manager on Windows. These tools can provide system-wide I/O metrics, including disk reads and writes by the PostgreSQL process.
    For example, on Linux, you can run the following command to monitor disk I/O for the PostgreSQL process: iostat -xk 1 | grep postgres This command will display real-time I/O metrics for the PostgreSQL process.

Remember that monitoring I/O metrics can help identify performance bottlenecks and optimize your PostgreSQL database for better performance. Consider using a combination of these methods to gain a comprehensive understanding of your system’s I/O activity.

PotgreSQL: How to display PostgreSQL Server sessions

You can display the active sessions (connections) on a PostgreSQL server by querying the pg_stat_activity view. This view provides information about the currently active connections and their associated queries. Here’s how you can use it:

  1. Connect to PostgreSQL: Start by connecting to your PostgreSQL server using the psql command-line client or another PostgreSQL client of your choice. You may need to provide the appropriate username and password or other authentication details.bashCopy codepsql -U your_username -d your_database_name
  2. Query pg_stat_activity: Once connected, you can query the pg_stat_activity view to see the active sessions. You can run the following SQL query: SELECT * FROM pg_stat_activity; This query will return a list of all active sessions, including information such as the process ID (pid), username (usename), database (datname), client address (client_addr), and the SQL query being executed (query). The state column provides the current state of each session, which can be helpful for diagnosing issues.
  3. Filter and Format the Output: If you want to filter the results or display specific columns, you can modify the query accordingly. For example, to see only the username, database, and query being executed, you can use the following query:SELECT usename, datname, query FROM pg_stat_activity; You can also use WHERE clauses to filter the results based on specific criteria. For instance, to see only sessions with a specific application name, you can do: SELECT * FROM pg_stat_activity WHERE application_name = 'your_application_name';
  4. Exit psql: After viewing the active sessions, you can exit the PostgreSQL client by typing: \q

This will return you to the command line.

Keep in mind that pg_stat_activity provides a snapshot of active sessions at the time you run the query. If you want to continuously monitor sessions in real-time, you may want to use monitoring tools or automate queries to periodically check the pg_stat_activity view.

Monitoring Performance of a PostgreSQL Database

Monitoring the performance of a PostgreSQL server is crucial to ensure that it’s running efficiently and to identify potential issues before they become critical. Here are steps and tools you can use to monitor the performance of a PostgreSQL server:

1. PostgreSQL Logs:

  • PostgreSQL generates log files that contain valuable information about the server’s activity and potential issues. You can find these log files in the PostgreSQL data directory, typically located at /var/log/postgresql/ on Linux.
  • Review these logs regularly to look for errors, warnings, and other noteworthy events.

2. PostgreSQL’s Built-in Monitoring:

  • PostgreSQL provides several system views and functions that can be used to monitor performance. Some useful views include pg_stat_activity, pg_stat_statements, and pg_stat_bgwriter. You can query these views to gather information about active connections, query statistics, and the state of background processes.
  • Example query to see active connections: SELECT * FROM pg_stat_activity;

3. pg_stat_statements:

  • If you haven’t already enabled the pg_stat_statements extension, consider doing so. This extension tracks query execution statistics, which can be invaluable for identifying slow or resource-intensive queries.
  • Enable the extension in your PostgreSQL configuration (postgresql.conf) and restart PostgreSQL.
  • Query pg_stat_statements to analyze query performance.

4. Performance Monitoring Tools:

  • There are various third-party monitoring tools that can help you track PostgreSQL performance in real-time, visualize data, and set up alerts. Some popular options include:
    • pgAdmin: A graphical administration tool that includes performance monitoring features.
    • pg_stat_monitor: An open-source PostgreSQL monitoring tool with a web interface.
    • Prometheus and Grafana: A powerful combination for collecting and visualizing PostgreSQL metrics. You can use the pg_prometheus extension to export metrics to Prometheus.
    • DataDog, New Relic, or other APM tools: Commercial monitoring tools that offer PostgreSQL integrations.

5. PostgreSQL Configuration Tuning:

  • Review and adjust PostgreSQL configuration settings (postgresql.conf) based on your server’s hardware and workload. Key parameters to consider include shared_buffers, work_mem, and max_connections. Tweaking these settings can have a significant impact on performance.

6. Resource Usage:

  • Monitor system resource usage (CPU, memory, disk I/O) using system-level monitoring tools like top, htop, or dedicated server monitoring solutions. High resource utilization can indicate performance bottlenecks.

7. Slow Query Log:

  • Enable PostgreSQL’s slow query log (log_statement = 'all' and log_duration = 0 in postgresql.conf) to log slow queries. This can help you identify and optimize problematic queries.

8. Vacuum and Maintenance:

  • Regularly run the VACUUM and ANALYZE commands to optimize table and index performance. You can automate this process using tools like autovacuum.

9. Database Indexing:

  • Ensure that your database tables are appropriately indexed, as missing or inefficient indexes can lead to slow query performance.

10. Query Optimization: – Use the EXPLAIN command to analyze query execution plans and identify opportunities for optimization. Make use of appropriate indexes, rewrite queries, and consider caching where applicable.

11. Set Up Alerts: – Configure monitoring alerts to be notified of critical issues promptly. This can help you proactively address performance problems.

12. Regular Maintenance: – Continuously monitor and fine-tune your PostgreSQL server to adapt to changing workloads and requirements.

Remember that PostgreSQL performance tuning is an ongoing process, and it may require periodic review and adjustments as your workload evolves. Monitoring and optimizing your PostgreSQL server is essential to ensure that it performs optimally and meets the needs of your applications.

How to upgrade a PostgreSQL Server

1. Backup your existing database: Before performing any upgrades, it’s essential to create a backup of your existing PostgreSQL database to prevent data loss in case something goes wrong. You can use the pg_dump utility to create a backup of your database.

pg_dump -U your_username -d your_database_name -f backup_file.sql

2. Check system requirements: Ensure that your system meets the hardware and software requirements for the new version of PostgreSQL you plan to install. You can find this information in the PostgreSQL documentation.

3. Review release notes: Carefully read the release notes for the version you want to upgrade to. This will provide information about changes, potential incompatibilities, and any specific upgrade instructions.

4. Install the new PostgreSQL version:

  • On Linux, you can use the package manager specific to your distribution to install PostgreSQL. For example, on Ubuntu, you can use apt, while on CentOS, you can use yum.
  • On macOS, you can use Homebrew or download and install the official PostgreSQL package.
  • On Windows, download and run the installer from the official PostgreSQL website.

5. Stop the old PostgreSQL server: Before you can perform the upgrade, you must stop the old PostgreSQL server. You can use the following command:

sudo systemctl stop postgresql

6. Upgrade the PostgreSQL data directory:

  • Use the pg_upgrade utility to upgrade your data directory. This tool is provided by PostgreSQL and is designed to facilitate the upgrade process.
  • Here is an example of how to use pg_upgrade:

pg_upgrade -b /path/to/old/bin -B /path/to/new/bin -d /path/to/old/data -D /path/to/new/data

Replace /path/to/old/bin, /path/to/new/bin, /path/to/old/data, and /path/to/new/data with the actual paths to your old and new PostgreSQL binaries and data directories.

7. Verify the upgrade: After running pg_upgrade, you should test your upgraded PostgreSQL database to ensure it functions correctly. Connect to the new database using the PostgreSQL client (psql) and perform some basic queries to confirm that everything is working as expected.

8. Update your applications: If you have any applications or scripts that interact with your PostgreSQL database, make sure they are compatible with the new version. You might need to update database drivers or modify queries if there are any breaking changes.

9. Start the new PostgreSQL server: Once you are confident that the upgrade was successful and your applications are working correctly with the new version, you can start the new PostgreSQL server:

sudo systemctl start postgresql

10. Monitor and optimize: After the upgrade, monitor the performance of your PostgreSQL server and make any necessary optimizations. This may include adjusting configuration settings, indexing, and query optimization.

Remember that upgrading a production database is a critical task, so always perform it with caution and consider testing the process in a development or staging environment before upgrading your production database.