Client Profile
Client is a leading African fintech and mobile payments platform enabling users and businesses to send, receive and manage money digitally. Founded with a mission to provide simple financial access for everyone, their platform powers payments for individuals, SMEs, enterprises and third-party platforms through various products.
The company processes trillions of Naira annually, supports millions of users and enables transactions across Nigeria’s financial ecosystem. With offerings covering personal finance, business payments, agent networks and enterprise payment infrastructure, Client plays a key role in driving digital financial inclusion across Africa.
Business Challenge
As Client expanded their digital payment platforms and transaction volume, maintaining high availability and performance of mission-critical services became increasingly challenging. The engineering and operations teams lacked complete real-time visibility across applications, databases, Kubernetes workloads, and underlying cloud infrastructure.
Critical issues such as pod failures, API latency spikes, sudden CPU and memory consumption, database performance bottlenecks, and deployment regressions were often detected late — only after impacting users. Logs and metrics were scattered across different tools, making root cause analysis slow and manual. Without automated alerting and health dashboards, the team was forced to rely on reactive troubleshooting and manual monitoring, leading to longer incident resolution times and potential risk to payment uptime, customer experience, and compliance.
Hence client required a unified observability solution with 24×7 monitoring to proactively detect issues, ensure application stability, analyze deployments, and maintain service reliability across multiple high-volume payment applications.
LogusIMS Solution
LogusIMS deployed a complete enterprise-grade observability framework built on tools viz., Grafana, Prometheus, OpenSearch and OverOps enabling full-stack monitoring across Client’s applications and infrastructure
Key elements of the solution
- 24×7 Monitoring & Support:
- LogUs IMS monitoring team proactively analyzes dashboards, alerts and application stability round the clock
- Immediate action on pod restarts, node failures, DB saturation, high CPU/memory and critical errors
- Continuous health checks and preventive maintenance reduce incident frequency
- Centralized Monitoring & Dashboards:
- Integrated Prometheus with exporters for Kubernetes, VMs, JVM, databases and custom application metrics
- Built Grafana dashboards for system health, application KPIs, transaction metrics and business analytics
- Enabled real-time visibility for engineering, DevOps and support teams
- Automated Alerting & Incident Response:
- Configured Prometheus Alertmanager with escalation alerts
- Automated notifications for API latency spikes, pod crashes, node failures, out-of-memory events, DB errors, VPN drops and deployment failures
- Alerts routed to Slack, email and NOC channels
- Centralized Logging & Error Intelligence:
- All logs shipped into OpenSearch via Logstash for fast search and RCA
- OverOps integrated to detect code-level exceptions and deployment-related issues
- Deployment Observability:
- Every deployment is tracked for error spikes
- Helps identify regressions instantly and prevent customer impact
With this implementation, team achieved real-time operational awareness, faster troubleshooting, improved uptime and greater confidence in scaling its digital payment services.
Overall Benefits
- Business Benefits:
- Improved reliability for payment transactions and merchant operations
- Reduced downtime risk protects revenue and customer experience
- Faster remediation prevents customer-visible failures
- Better visibility ensures stability even during traffic/transaction spikes
- Operational Improvements:
- 30–50% faster incident resolution time due to centralized logs, metrics and dashboards
- ~99.9% service uptime enabled through proactive 24×7 monitoring
- Immediate detection of service degradation (latency, pod crash, CPU/memory spikes)
- Reduced manual effort for troubleshooting and deployment validation
- Engineering Efficiency:
- 40% reduction in time spent analyzing failures or searching logs
- Faster RCA with correlated metrics, logs and errors via OpenSearch & OverOps
- DevOps teams get instant alerts for regressions after a deployment
- Easier capacity planning with resource utilization dashboards
- Process & Quality Improvements:
- Unified monitoring standard implemented across multiple applications
- Automated CI/CD checks and deployment health validation
- Continuous feedback from alerting prevents repeated failures
- Predictive monitoring helps identify issues before impact
Technology/Tools
| # | Category | Technologies / Tools Used |
| 1 | Monitoring & Observability | Grafana, Prometheus, Alertmanager, Node Exporter, JVM Exporter, Kube-State Metrics |
| 2 | Logging & Error Analysis | OpenSearch, Logstash, OverOps |
| 3 | Infrastructure & Cloud | Kubernetes, Docker, Azure Virtual Machines, Linux Servers |
| 4 | CI/CD & Automation | Jenkins / GitHub Actions, Gradle, Shell Scripts (build.sh, test.sh), OWASP Dependency Check, Ansible |
| 5 | Networking & Runtime Components | NGINX Ingress Controller, Infinispan Cache Cluster, VPN Monitoring |
| 6 | Application Layer | Java / Spring Boot microservices |