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from fragmented monitoring to real-time resilience.

Powering a Serverless Trading Platform with Observability

Cloud Elemental helped a leading energy provider enhance resilience and accelerate incident response across its serverless trading platform through a scalable, real-time observability model powered by Dynatrace and AWS CloudWatch, seamlessly integrated with ServiceNow.

The Client

Our client is a large UK-based energy provider operating a business-critical, cloud-native trading platform with high availability, governance, and operational resilience requirements.

As part of launching a new serverless application, the organisation recognised that traditional monitoring approaches were no longer sufficient to provide the real-time visibility required in a modern AWS environment. With platform reliability and incident response under increasing scrutiny, they sought to strengthen observability, improve workflow integration, and build greater confidence in their disaster recovery readiness.

Cloud Elemental was engaged to design and implement a scalable, enterprise-ready observability model that would enhance platform transparency, accelerate issue detection, and align incident management with existing operational tooling and governance standards.

The Challenge

As the client prepared to launch a business-critical serverless trading platform, ensuring resilience and operational readiness became a priority. However, several key challenges limited visibility, responsiveness, and long-term scalability.

Four specific operational challenges were identified:

Limited Real-Time Visibility

While AWS CloudWatch logs were available, there was no unified, intuitive view of platform health across serverless functions. This made it difficult to quickly detect performance degradation or emerging issues before user impact.

No Standardised Alerting Model

Alarm thresholds were not consistently defined or aligned across tools. Without clearly structured alert logic, teams lacked confidence that critical anomalies would surface in a timely and actionable way.

Fragmented Incident Workflows

Notification and ticketing processes were not fully integrated across Dynatrace, Slack, ServiceNow, and Jira. This led to manual coordination between teams and increased time to resolution during incidents.

Limited Operational Documentation & Ownership

There was no consolidated operational playbook outlining alarm logic, ownership models, or escalation paths. This created risk for onboarding, knowledge transfer, and long-term sustainability as the platform scaled.

The CE Approach

Cloud Elemental applied a structured methodology to strengthen observability, streamline incident response, and build disaster recovery readiness for the client’s serverless trading platform.

Cloud Readiness Assessment

  • Reviewed serverless architecture and existing CloudWatch integrations

  • Identified observability blind spots across Lambda functions

  • Assessed alignment with internal tooling, workflows, and governance models

  • Clarified gaps in real-time visibility and defined the need for proactive alerting

Solution Blueprinting

  • Designed an integrated observability framework using Dynatrace and AWS CloudWatch

  • Defined clear, actionable alarm thresholds aligned to function groupings

  • Architected integrations across Slack, ServiceNow, and Jira

  • Produced dashboard structures and operational documentation to support adoption

Feasibility & Governance Validation

  • Validated alarm logic against internal compliance and governance standards

  • Reviewed data handling and incident lifecycle processes

  • Confirmed technical integration viability across systems

  • De-risked rollout by aligning with enterprise operational requirements

Blueprint Planning & Handover

  • Developed structured documentation and dashboard configuration guides

  • Created a Duty Engineer playbook with defined ownership and escalation paths

  • Delivered a roadmap for enhancements such as dynamic thresholding

  • Established a scalable observability model for future platforms

This phased approach ensured technical effectiveness while embedding long-term ownership, operational clarity, and resilience.

Our Solution

Serverless Observability via Dynatrace

The client had already configured CloudWatch to feed AWS Lambda logs into Dynatrace. Our contribution focused on defining clear alert thresholds and improving visibility by aligning alarms with intuitive dashboard visualisations.

  • Dashboards represented Lambda execution times by function group, with thresholds mirroring Dynatrace alarm configurations – ensuring that both channels reflected the same issue clearly.
  • Static thresholds were applied per function, with an eye to potential future migration to dynamic, ML-driven thresholds.
  • Recurring issues and performance bottlenecks were surfaced through historical metrics and trend analysis.

Operational Tooling & Handover

Operational documentation and visibility were key deliverables of this engagement:

  • A Confluence page catalogued all configured Lambda functions, linked to relevant Slack channels, Dynatrace dashboards, and ServiceNow tickets.
  • Additional documentation explained the alarm threshold logic, Dynatrace dashboard setup, and Slack integration details.
  • While per-Lambda remediation runbooks were flagged as a future enhancement, initial documentation was structured to support this direction.

Real-Time Incident Notification & Integration

To ensure critical issues were flagged and followed up effectively, we supported a multi-layered incident notification process.

  • Slack integration enabled Dynatrace alarms to alert teams in real-time via dedicated support channels.
  • Jira synchronisation ensured tickets raised in ServiceNow appeared in Jira, aligning with the client’s engineering workflows.
  • ServiceNow integration triggered ticket creation based on predefined metric thresholds and naming conventions.
  • A Duty Engineer Playbook was developed to clearly assign responsibility and rotate on-call ownership for timely response.

Our Results

By enhancing observability and establishing real-time incident detection, Cloud Elemental empowered the client to improve platform reliability, reduce response times, and gain greater operational clarity. The solution addressed immediate monitoring gaps while creating a robust foundation for future service evolution and engineering efficiency.

Faster Issue Detection

Alarms reduced incident detection time from hours to minutes by surfacing critical issues in real time, enabling rapid intervention before wider impact.

Improved Platform Reliability

Proactive monitoring flagged performance bottlenecks early, increasing uptime, strengthening system stability, and improving trust in the platform.

Unified Operational Visibility

Integrated dashboards and cross-tool workflows aligned IT and engineering teams around a single source of truth, ensuring clear ownership, routing, and traceability of incidents across Slack, ServiceNow, and Jira.

Scalable Observability Framework

Documentation, dashboard templates, and structured processes created a reusable observability model that can be extended across future platforms and evolving service requirements.

This engagement not only fortified resilience but also created a reusable blueprint for the client’s future applications.

Cloud Elemental’s involvement set the groundwork for future initiatives, including dynamic thresholding, expanded service mapping in ServiceNow, and development of remediation playbooks. Whilst some of these capabilities remain on the roadmap, the client now benefits from a resilient, transparent, and collaborative incident detection model aligned with its growing Cloud maturity.

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