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New Relic

Score7.8 out of 10

307 Reviews and Ratings

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What is New Relic?

New Relic is a SaaS-based web and mobile application performance management provider for the cloud and the datacenter. They provide code-level diagnostics for dedicated infrastructures, the cloud, or hybrid environments and real time monitoring.

Categories & Use Cases

Reviews

What users are saying about New Relic.
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New Relic Comprehensive Performance Monitoring tool

Incentivized
Verified User
Administrator in Information Technology (51-200 employees employees)

Use Cases and Deployment Scope

We use New Relic to monitor the performance and health of our applications, infrastructure, cloud services across various environments. It helps us quickly detect and troubleshoot issues, optimize application performance, and ensure a smooth user experience. The platform provides end-to-end visibility across our stack from backend services to frontend user interactions and integrates with our alerting and incident management tools. It helps us to reduce the downtime of our applications and also to reduce the MTTD and MTTR.

Pros

  • It gives us insights of applications, infrastructure, clouds very well.
  • The alerting system in New Relic helps us to easily identify the root cause which reduces the MTTR.
  • It has new features related to AI which helps to troubleshoot any problem in a very short time it gives future predictions also.

Cons

  • The distribution system of New Relic, currently it is available for APM and browser only so it will be helpful if we can put this feature in other services also.
  • Earlier New Relic UI is working fine, but now it is taking too much time to load the complete UI so New Relic can improve in that.

Return on Investment

  • The positive impact which newrelic gives us that is, it reduced our MTTD, MTTR. Through newrelic we can easily monitor our infrastructures performance and utilization status. We just need to integrate the services with newrelic and newrelic captures all the telemetry form that service, through that data we can visualize proper dashboards also that helps the technical team to analyze their systems quickly.
  • Through the help of its agent we can easily trace the calls in application and also we show the complete sessions of any user.
  • Its Kubernetes monitoring feature is also very useful which gives us insights for all the k8s components, we can easily troubleshoot if we are getting any issue in that.

Usability

Alternatives Considered

Datadog, Azure Monitor and Amazon CloudWatch

Other Software Used

Azure Monitor, Amazon CloudWatch

Optimizing performance with New Relic

Incentivized
Verified User
Engineer in Engineering (201-500 employees employees)

Use Cases and Deployment Scope

I have been using New Relic for last 2.5years, and I have used it for different purposes like Infrastructure monitoring, APM Monitoring, Browser Monitoring, Mobile monitoring and etc. I have seen so many good features of New Relic as compare to other observability tools. It works on the MELT (Metrics, Events, Logs, Traces) data to provide the observability solutions as per our requirement. I have used it in different types of business requirements like for complete session tracking and its errors, for applications and its infrastructure downtime status. It has features like alerts, service levels, dashboards, synthetic monitors, etc. which helps us to track the issues of our application environment before they occurred with with real users. They also recently launched few more features like transaction 360, eAPM, Agent Control, pipeline control, cloud cost intelligence, Intelligence Response, Security Rx etc. which helps in various domains like finops through telling us the cloud cost and its utilization, Security of our infra and applications through Security Rx which captures vulnerability of Applications and infrastructure, Intelligence response which helps to easily tell the root cause analysis of alerts or any errors which helps us to reduce the MTTD and MTTR, etc.

Pros

  • It's recently launched features pipeline control which gives us full control of our data like how much data we want to send to New Relic it has filteration in two levels one is at our environment, that is gateway control and another is in New Relic env, that is cloud control. I personally like this feature.
  • Its observability as a code feature like through the help of terraform we can create New Relic resources like alerts, service levels, dashboards, drop rules, parsing rules, workloads etc. and also we can integrate major clouds also through terraform.
  • The custom visualization feature of New Relic, through the help of this, we can create custom dashboards based on React.

Cons

  • Sometimes I have seen some glitches in data like some amount of data is missing so they can work on it.

Return on Investment

  • Yes, it always gives us positive impact like if I have some issues in my application or if I need to update any resources for security concerns so it always helped me beforehand for those.

Alternatives Considered

Dynatrace, Splunk Application Performance Monitoring (APM), Splunk Infrastructure Monitoring, Grafana, Amazon CloudWatch and Azure Monitor

Other Software Used

HashiCorp Terraform, GitHub, AWS Lambda, Azure Functions, Microsoft Teams, Datadog

New Relic Observability Enablement

Incentivized
Verified User
Engineer in Information Technology (201-500 employees employees)

Use Cases and Deployment Scope

We use the New Relic for the observability implementations for the applications like frontend and backend. Integrating the cloud account and services. It helps in understanding the performance of the applications and troubleshooting the apps if any error's occurs. In the New Relic it helps in setting up the alerts and getting notified as per the service breaches the conditions. Building the dashboards for visualizing the insights. creating the synthetics for availability of the endpoints and proactive monitoring and checking the status of the apps.

Pros

  • Template variable dashboarding and filtering the data
  • Workloads and checking the status of the apps in one place related to the one env or the one project
  • Support of instrumentation with the third party tools
  • Alerting and getting notified to the users via channels

Cons

  • API calls for the third party tools latency sometimes slow it can be improved
  • Instrumentation steps can given in more clear format
  • sometimes there is slight in the data visibility that can worked on for the spot data

Return on Investment

  • By this tools we are able to know the overall performance's of the services
  • Getting notified whenever a system or services behaves abnormal
  • Helping client to understand the data visually and improve the performance of the services and systems

Usability

Alternatives Considered

Datadog, Splunk Observability Cloud, Amazon CloudWatch and Dynatrace

Other Software Used

Amazon CloudWatch, Datadog, Azure Monitor

End-to-end monitoring and automation for efficiency and performance gain

Incentivized
Alex Jones
Energy Engineer in Engineering at nLine (51-200 employees employees)

Use Cases and Deployment Scope

we monitor our energy management systems, assuring the realtime integrity of Big Data we generate from IoT devices and SCADA networks. It allows us to catch underperformance as soon as possible, reduce downtime, and ensure system availability. We use its APM and infrastructure monitoring for to enable energy audits, load forecasting, and keep our client facing analytics dashboards running smooth.

Pros

  • New Relic APM allows us to follow up transactions across services and trace performance bottlenecks in real-time, crucial when monitoring the processing of energy loads or predictive maintenance algorithms.
  • It gives us deep visibility into our cloud servers, containers and IOT gateways, so we can catch CPU spikes or memory leaks which can impact the data we ingest from the field devices.
  • We develop custom dashboards for monitoring trends of power consumption, abnormality in sensors and API health. In conjunction with alerting, it makes sure we are fixing issues before customers even see them.

Cons

  • And while powerful, building tailored dashboards with organ-specific metrics (such as energy load variance across regions) can be difficult to navigate. The UI isn't as drag-and-drop easy, and query-based widgets typically involve some trial and error for non-devs.
  • Alerts may be hypersensitive or over general. I We often get a spam of non-critical alerts while doing load testing, all overhauling to me alone and making it difficult to identify actual issues especially in energy systems where spikes are very common.
  • With our expanding fleet of Iot devices, the per-host pricing model is becoming expensive, quickly. More detailed billing based on microservices, or that works at sensor level, would make it more adaptable for energy platforms.

Return on Investment

  • I have detected issues early and we have averted many unplanned outages in our power system that would have resulted in SLA penalties and angry clients.
  • Engineers spend less time debugging and more time building, reducing project lead times.
  • Consistent delivery and transparent real time visibility into performance has increased client confidence and therefore straight business on long term contract renewals.

Other Software Used

Datadog, Jenkins

Good value for money easy to set up.

Incentivized
Anubhav MalikView profile
CTO in Engineering at Weekday (51-200 employees employees)

Use Cases and Deployment Scope

We use New Relic heavily for logging, performance analysis and observability. It gives us a good searchable dump of all logs in one place, which we don't have to worry about maintaining ever, along with all the p90, p99 metrics and error rates for all APIs in one place. Alerting could be a little bit better though.

Pros

  • Slow SQL trace detection
  • Log collection
  • API error rate monitoring

Cons

  • Logs are limited to low sizes causing incomplete logs
  • Alerting integration with slack and golden signals is not straightforward
  • In Node Js, a lot of spans are just Unknown application code which is not at all helpful while analysing traces

Return on Investment

  • We were able to quickly identify our most time consuming APIs. In some cases we were able to bring down times for some apis from 4s to 200ms.
  • We were able to identify our slowest database queries and optimize them for quicker response times.

Alternatives Considered

Datadog, Sentry and Elasticsearch

Other Software Used

Sentry, Elasticsearch, Azure Kubernetes Service (AKS)

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