Algorithmia
Managed MLflow
neptune.ai
MCenter
5Analytics
Iterative.ai
Datatron
Spell
Dashbird
Lumigo
Epsagon
Datadog
NewRelic
AWS Lambda
Amazon CloudWatch
AWS X-Ray
Dashbird is an observability, debugging, and intelligence platform designed specifically to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment fast, securely, and with ease. It’s free to use for up to 1M invocations and doesn’t require any code changes.
Dashbird fills the gaps left by CloudWatch and other traditional monitoring tools by offering enhanced out-of-the-box monitoring, operations, and actionable insights tools for architectural improvements, all in one place.
Full observability covered for AWS services: Lambda, API Gateway, DynamoDB, SQS, ECS, Step Functions, Kinesis, HTTP API Gateway, RDS, SNS, OpenSearch, ELB.
Dashbird’s approach is fairly simple, all the mission-critical data of your entire serverless system is placed in a single dashboard giving you a birds-eye-view of the entire system activity. Moreover, you get immediate alerts on any errors or warnings that may arise and get pointed to the exact point of failure in the system so it can be resolved fast.
The 3 core pillars of Dashbird are:
Real-time end-to-end serverless observability Automatic Failure Detection Continuous Well-Architected reports on your entire infrastructure
Algorithmia DashbirdNo features have been listed yet.
Based on our record, Dashbird seems to be a lot more popular than Algorithmia. While we know about 59 links to Dashbird, we've tracked only 5 mentions of Algorithmia. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 3 years ago
There's more to come at Dashbird, as we're already building more features to help you run the best possible AppSync endpoints. This includes a set of well-architected insights to guide you with best practices. - Source: dev.to / almost 2 years ago
Observability in serverless Tools like Datadog, Splunk, Thundra.io, New Relic, and Dashbird make monitoring and debugging serverless applications easy. They collect metrics, logs, and traces from AWS Cloudwatch and X-ray. - Source: dev.to / almost 2 years ago
With its latest release, Dashbird added support for APIG's HTTP APIs. All your HTTP APIs are automatically monitored after installing Dashbird into your AWS account. You need to deploy a CloudFormation template to set up Dashbird integration; it doesn't require any code changes! - Source: dev.to / almost 2 years ago
I decided to try out Dashbird because it’s free and seems promising. They’re not asking for a credit card either, making it a “why not try it out” situation. - Source: dev.to / about 2 years ago
With the emergence of managed and distributed services, the monitoring landscape will have to go through a significant change to keep up with modern cloud applications. Currently, devops overhead is one of the biggest obstacles for companies looking to use serverless in production and rely on it for mission-critical applications. Our team at Dashbird is hoping to solve that one problem at a time. - Source: dev.to / about 2 years ago
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
Lumigo - With one-click distributed tracing, Lumigo lets developers effortlessly find and fix issues in serverless and microservices environments.
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
Epsagon - Track costs and fix your serverless application.
MCenter - Machine Learning Operationalization
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
