What is Bigpanda and what are its top alternatives?
Top Alternatives to Bigpanda
- PagerDuty
PagerDuty is an alarm aggregation and dispatching service for system administrators and support teams. It collects alerts from your monitoring tools, gives you an overall view of all of your monitoring alarms, and alerts an on duty engineer if there's a problem. ...
- Datadog
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog! ...
- Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...
- OpsGenie
OpsGenie is a cloud-based service for dev & ops teams, providing reliable alerts, on-call schedule management, and escalations. OpsGenie integrates with monitoring tools & services and ensures that the right people are at the right time. ...
- VictorOps
VictorOps is a real-time incident management platform that combines the power of people and data to embolden DevOps teams so they can handle incidents as they occur and prepare for the next one. ...
- Healthchecks.io
Healthchecks.io is a monitoring service for your cron jobs, background services and scheduled tasks. It works by listening for HTTP "pings" from your services. You can set up various alert methods: email, Slack, Telegram, PagerDuty, etc. ...
- Cronitor
Monitoring systems are often complex and require a strong sysadmin background to properly configure and maintain. Cronitor replaces all this with a simple service that anyone can set up. Receive email/sms notifications if your jobs don't run, run too slow, or finish too quickly. ...
- Squadcast
It is an end-to-end incident response platform that helps tech teams adopt SRE best practices to maximize service reliability, accelerate innovation velocity and deliver outstanding customer experiences. ...
Bigpanda alternatives & related posts
PagerDuty
- Just works54
- Easy configuration23
- Awesome alerting hub14
- Fantastic Alert aggregation and on call management11
- User-customizable alerting modes9
- Awesome tool for alerting and monitoring. Love it4
- Most reliable out of the three and it isn't even close3
- Expensive7
- Ugly UI3
related PagerDuty posts
Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.
We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.
Data science and engineering teams at Lyft maintain several big data pipelines that serve as the foundation for various types of analysis throughout the business.
Apache Airflow sits at the center of this big data infrastructure, allowing users to “programmatically author, schedule, and monitor data pipelines.” Airflow is an open source tool, and “Lyft is the very first Airflow adopter in production since the project was open sourced around three years ago.”
There are several key components of the architecture. A web UI allows users to view the status of their queries, along with an audit trail of any modifications the query. A metadata database stores things like job status and task instance status. A multi-process scheduler handles job requests, and triggers the executor to execute those tasks.
Airflow supports several executors, though Lyft uses CeleryExecutor to scale task execution in production. Airflow is deployed to three Amazon Auto Scaling Groups, with each associated with a celery queue.
Audit logs supplied to the web UI are powered by the existing Airflow audit logs as well as Flask signal.
Datadog, Statsd, Grafana, and PagerDuty are all used to monitor the Airflow system.
Datadog
- Monitoring for many apps (databases, web servers, etc)135
- Easy setup106
- Powerful ui86
- Powerful integrations82
- Great value69
- Great visualization53
- Events + metrics = clarity45
- Custom metrics40
- Notifications40
- Flexibility38
- Free & paid plans18
- Great customer support15
- Makes my life easier14
- Adapts automatically as i scale up9
- Easy setup and plugins8
- Super easy and powerful7
- AWS support6
- In-context collaboration6
- Rich in features5
- Docker support4
- Cost4
- Automation tools3
- Source control and bug tracking3
- Simple, powerful, great for infra3
- Cute logo3
- Expensive3
- Easy to Analyze3
- Full visibility of applications3
- Monitor almost everything3
- Best than others3
- Good for Startups2
- Free setup2
- Best in the field2
- APM1
- Expensive17
- No errors exception tracking4
- External Network Goes Down You Wont Be Logging2
- Complicated1
related Datadog posts
Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.
We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.









We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.
We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.
We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.
You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?
- Alert system based on custom query results2
- API for searching logs, running reports2
- Query engine supports joining, aggregation, stats, etc2
- Ability to style search results into reports1
- Query any log as key-value pairs1
- Splunk language supports string, date manip, math, etc1
- Granular scheduling and time window support1
- Custom log parsing as well as automatic parsing1
- Dashboarding on any log contents1
- Rich GUI for searching live logs1
- Splunk query language rich so lots to learn1
related Splunk posts
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
- Two-way slack integration7
- Strong API4
- Solid scheduling and team management support4
- Two-way nagios integration3
- Strong, easy, fast, fits3
- Free tier2
- Complete Incident Response Orchestration Platform2
related OpsGenie posts
- The transmogrifier is a game changer7
- Great Team, Great Product6
- Free tier5
- Much better than ANY of the alternatives. Todd is GREAT3
- Great tiered escalation management3
- Android app with Wear integration2
- On-call routing and the timeline is brilliant2
- Awesome Team always updating1
- Nice UI1
related VictorOps posts
- Can be self-hosted3
- Great value2
- Free tier2
- Easy to understand2
related Healthchecks.io posts
- Quick and helpful support2
- Simple and direct1
- Pricey0
related Cronitor posts
- Easy Configuration2
- Intuitive UI / UX2
- Lots of Integrations2
related Squadcast posts
I'm currently on PagerDuty, but I'm about to add enough users to go out of the starter tier, which will dramatically increase my license cost. PagerDuty is, in my experience, quite clunky, and I'm looking for alternatives. Squadcast is one I've found, and another is xMatters. Between the three, I'm currently leaning towards xMatters, but I'd like to know what people suggest.