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What is Honeycomb?

Transform your log management practices with Honeycomb, a platform meticulously crafted for modern development teams that seek to extract valuable insights into application performance while improving log management efficiency. Honeycomb’s fast query capabilities allow you to reveal concealed issues within your system’s logs, metrics, and traces, employing interactive charts that deliver thorough examinations of raw data with high cardinality. By establishing Service Level Objectives (SLOs) that align with user priorities, you can minimize unnecessary alerts and concentrate on critical tasks. This streamlined approach not only reduces on-call duties but also accelerates code deployment, ultimately ensuring high levels of customer satisfaction. You can pinpoint the root causes of performance issues, optimize your code effectively, and gain a clear view of your production environment in impressive detail. Our SLOs provide timely alerts when customers face challenges, facilitating quick investigations into the underlying issues—all managed from a unified interface. Furthermore, the Query Builder allows for seamless data analysis, enabling you to visualize behavioral patterns for individual users and services, categorized by various dimensions for enriched analytical perspectives. This all-encompassing strategy guarantees that your team is equipped to proactively tackle performance obstacles while continuously enhancing the user experience, thus fostering greater engagement and loyalty. Ultimately, Honeycomb empowers your team to maintain a high-performance environment that is responsive to users' needs.

What is Amazon SageMaker Debugger?

Improve machine learning models by capturing real-time training metrics and initiating alerts for any detected anomalies. To reduce both training time and expenses, the training process can automatically stop once the desired accuracy is achieved. Additionally, it is crucial to continuously evaluate and oversee system resource utilization, generating alerts when any limitations are detected to enhance resource efficiency. With the use of Amazon SageMaker Debugger, the troubleshooting process during training can be significantly accelerated, turning what usually takes days into just a few minutes by automatically pinpointing and notifying users about prevalent training challenges, such as extreme gradient values. Alerts can be conveniently accessed through Amazon SageMaker Studio or configured via Amazon CloudWatch. Furthermore, the SageMaker Debugger SDK is specifically crafted to autonomously recognize new types of model-specific errors, encompassing issues related to data sampling, hyperparameter configurations, and values that surpass acceptable thresholds, thereby further strengthening the reliability of your machine learning models. This proactive methodology not only conserves time but also guarantees that your models consistently operate at peak performance levels, ultimately leading to better outcomes and improved overall efficiency.

Media

Media

Integrations Supported

API3
AWS Lambda
AWS Marketplace
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Arch
Autodesk A360
Change Healthcare Data & Analytics
Cribl AppScope
Doctor Droid
Kamsa
Langtrace
MXNet
Parny
PyTorch
Slack
Terraform
Zenduty

Integrations Supported

API3
AWS Lambda
AWS Marketplace
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Arch
Autodesk A360
Change Healthcare Data & Analytics
Cribl AppScope
Doctor Droid
Kamsa
Langtrace
MXNet
Parny
PyTorch
Slack
Terraform
Zenduty

API Availability

Has API

API Availability

Has API

Pricing Information

$70 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Honeycomb.io

Date Founded

2016

Company Location

United States

Company Website

www.honeycomb.io

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Log Management

Archiving
Audit Trails
Compliance Reporting
Consolidation
Data Visualization
Event Logs
Network Logs
Remediation
Syslogs
Thresholds
Web Logs

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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