SaaSHub helps you find the best software and product alternatives Learn more →
Berglas Alternatives
Similar projects and alternatives to berglas
-
-
InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
-
terraform
Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
-
-
-
-
-
-
CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
-
-
infisical
Infisical is the open-source platform for secrets management, internal PKI, and SSH access.
-
-
-
-
-
-
-
nodejs-storage
Node.js client for Google Cloud Storage: unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archiving.
-
secrets-store-csi-driver
Secrets Store CSI driver for Kubernetes secrets - Integrates secrets stores with Kubernetes via a CSI volume.
-
-
-
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better berglas alternative or higher similarity.
berglas discussion
berglas reviews and mentions
Posts with mentions or reviews of berglas.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-04-07.
-
Generating images with Gemini 2.0 Flash from Google
If saving locally, Python developers can also choose to save it to .env instead of settings.py but would have to add use of the python-dotenv package to more closely mirror working in a Node.js environment. There's also the GCP Secret Manager as yet another option. Regardless of which technique you use, review the suggestions in the sidebar below to protect it!
-
Generate audio clips with Gemini 2.0 Flash
Like in previous code samples in this series, the API key is saved to settings.py. Alternatively, you can save your API key to the GOOGLE_API_KEY environment variable, or use the python-dotenv package, storing the API key in .env to more closely mirror working in a Node.js environment. There's also the GCP Secret Manager as yet another option.
-
The New Dev's Guide to Externalizing App Config
Cloud platforms provide tools like AWS Secrets Manager, Azure Key Vault, and Google Cloud Secret Manager for exactly this purpose. These services, which evolved from patterns Mitchell Hashimoto pioneered with Vault in 2015, store and encrypt your configuration.
-
How to deploy a Django app to Google Cloud Run using Terraform
Secret Manager: secure storage for sensitive data e.g passwords.
- How do you handle sensitive variables with a service-worker?
-
Increasing Your Cloud Function Development Velocity Using Dynamically Loading Python Classes
Google Secret Manager
-
Getting started using Google APIs: API Keys (Part 2)
API keys are easy to "leak" or compromise, so best to not only use the restrictions presented to you when you create them but physically protect them as well. Don't code them in plain-text, don't check them into GitHub, etc. Store them in a secure database or use a service like GCP Secret Manager.
-
Need some advice on API key storage
I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights.
-
Secure GitHub Actions by pull_request_target
In this post, I described how to build secure GitHub Actions workflows by pull_request_target event instead of pull_request event. Using pull_request_target, you can prevent malicious codes from being executed in CI. And by managing secrets in secrets management services such as AWS Secrets Manager and Google Secret Manager and access them via OIDC, you can restrict the access to secrets securely. To migrate pull_request to pull_request_target, several modifications are needed. And pull_request_target has a drawback that it's difficult to test changes of workflows, so it's good to introduce pull_request_target to repositories that require strong permissions in CI. For example, a Terraform Monorepo tends to require strong permissions for CI, so it's good to introduce pull_request_target to it.
-
Need Help with Deploying Directus on Google Cloud Platform (GCP)
If you want to make these secrets more secure and get versioning and access logs for them, you may want to switch to Secret Manager later on. They can still be exposed as environment variables to your code. It's a little more setup work, so start with the simple approach at the top.
-
A note from our sponsor - SaaSHub
www.saashub.com | 18 Apr 2025
Stats
Basic berglas repo stats
40
1,257
5.6
2 days ago
GoogleCloudPlatform/berglas is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of berglas is Go.
Sponsored
InfluxDB high-performance time series database
Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
influxdata.com