pgx
Grafana
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pgx | Grafana | |
---|---|---|
71 | 379 | |
9,414 | 60,279 | |
- | 1.5% | |
9.2 | 10.0 | |
8 days ago | 6 days ago | |
Go | TypeScript | |
MIT License | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pgx
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Setting up a Database Driver, Repository and Implementation of a transaction function for your Go App
Sometimes, backend developers tend to opt for an ORM library because it provides an abstraction between your app and the database and thus there is little or no need to write raw queries and migrations which is nice. However, if you want to get better at writing queries (SQL for example), you need to learn how to build your repositories without an ORM. To open a database handle, you can either do it directly from the database driver or do it from database/sql with the driver passed into it. I will be opening the connection with database/sql together with pgx which is a driver and toolkit for PostgreSQL. Walk with me.
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The DDD Hamburger for Go
The infrastructure layer contains the concrete implementation of the repository domain interface ActivityRepository in the struct DbActivityRepository. This repository implementation uses the Postgres driver pgx and plain SQL to store the activity in the database. It uses the database transaction from the context, since the transaction was initiated by the application service.
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Building RESTful API with Hexagonal Architecture in Go
For building the RESTful Point of Sale service API, I've considered and selected a combination of technologies that would work seamlessly together. For handling HTTP requests and responses, using the Gin HTTP web framework would make sense because I think it seems complete and popular among Go community too. To ensure data integrity and persistence, I'm using PostgreSQL database with pgx as the database driver, the reason I choose PostgreSQL because it is the most popular relational database to use in production and offers efficient Go integration. I'm also implementing caching using Redis with go-redis client library, which provides powerful in-memory data storage capabilities.
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Working with postgres in GO.
If you are willing to commit to working only with Postgres, I highly recommend pgx. Be sure you get the latest version github.com/jackc/pgx/v5. This gives you the full power of interacting with Postgres without going through an intermediate lowest-common-denominator library.
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How to Use Iris and PostgreSQL for Web Development
It uses pg package and pgx driver under the hood.
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Could I get a code review?
Starting off, is there any reason you're calling out to the CLI, instead of just using a Postgres driver like pgx? Shelling out to the command line should always be a last resort where possible as a software engineer.
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Why elixir over Golang
For maintaining state I use PostgreSQL. Driver: https://github.com/jackc/pgx (I use the pgxpools) Along with Sqlc for generating database models and allowing me to focus on just building queries in DBeaver. https://sqlc.dev/
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Make psql display settings on login
An example of what I'm looking for can be found here https://github.com/jackc/pgx/wiki/Getting-started-with-pgx-through-database-sql/c9f798b4d9a500fcf93931df2464af969d68f516
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Zig now has built-in HTTP server and client in std
Except pgx recommends using their native interface, not database/sql, for performance and extra features [0], so it's not that simple in practice.
[0]: https://github.com/jackc/pgx#choosing-between-the-pgx-and-da...
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Go Roadmap
pgx is “PostgreSQL driver and toolkit for Go”. Take a look at https://github.com/jackc/pgx
Grafana
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.
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Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.
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Monitoring, Observability, and Telemetry Explained
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
- Grafana: Open and composable observability and data visualization platform
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The Mechanics of Silicon Valley Pump and Dump Schemes
Grafana
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Reverse engineering the Grafana API to get the data from a dashboard
Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.
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Building an Observability Stack with Docker
So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:
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How to collect metrics from node.js applications in PM2 with exporting to Prometheus
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:
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Root Cause Chronicles: Quivering Queue
Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.
What are some alternatives?
sqlx - general purpose extensions to golang's database/sql
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
GORM - The fantastic ORM library for Golang, aims to be developer friendly
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
pq - Pure Go Postgres driver for database/sql
Heimdall - An Application dashboard and launcher
gomock - GoMock is a mocking framework for the Go programming language.
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
go-sql-driver/mysql - Go MySQL Driver is a MySQL driver for Go's (golang) database/sql package
Thingspeak - ThingSpeak is an open source “Internet of Things” application and API to store and retrieve data from things using HTTP over the Internet or via a Local Area Network. With ThingSpeak, you can create sensor logging applications, location tracking applications, and a social network of things with status updates.
sqlc - Generate type-safe code from SQL
uptime-kuma - A fancy self-hosted monitoring tool