
Amazon CloudWatch Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used Amazon CloudWatch
Kevin F.
Last position:
DevOps and Platform Engineer at DB Systel GmbH
- Error analysis and fixes including performance optimization of the in-house developed platform API
- Change and incident management in day-to-day operations
- Responsible for compliance with security and compliance requirements
- Vendor management for software development and maintenance
- Planning and execution of migration of legacy services to a cloud native platform
Role in the project: project staff, implementation team
Used skills: requirements analysis, IT service and application management, IT operations, error analysis and performance optimization, software maintenance and lifecycle management
Project environment: Cloud Native Platform (Kubernetes, Crossplane, AWS, ArgoCD, Grafana)
Uday V.
Last position:
Senior Full Stack Java Developer & DevOps Engineer at Deutsche Börse (DBAG)
Project: SCS (Settlement / Clearing Services)
Settlement platform serving multiple trading and clearing venues — counterparty risk safeguarding, settlement volume reduction, central risk management, and post-trade anonymity.
Technologies: Java 17, Spring Boot 3, Microservices, Spring Data JPA, SonarQube, Fortify (SCST), Mockito, Jenkins, OpenShift, Maven, Podman, GitHub, JIRA, Liquibase, Swagger, AMQP, Apache Camel, Terraform, PostgreSQL, Instana, Graylog.
- Identified and remediated CVEs in third-party libraries using SCA tooling, strengthening the security posture of production components.
- Maintained 90% code coverage with SonarQube, improving code quality and reducing production defects.
- Enabled mTLS for database authentication and message broker connections, enforcing encrypted, certificate-validated communication.
- Designed and deployed microservices with asynchronous, REST-based communication between components.
- Optimized a high-volume REST API (~200K requests) by reducing response time from 3s to 2s (33% improvement), boosting throughput and reliability under production load.
- Automated build and continuous integration pipelines using Maven and Jenkins.
- Orchestrated containerized workloads on Podman/OpenShift and governed schema evolution with Liquibase, ensuring reliable, repeatable deployments across all environments.
- Optimized Java code and implemented EHCache-based caching, improving application performance.
- Streamlined release management by governing application images, JAR versions, and dependencies through DBAG Artifactory, ensuring version consistency and audit traceability across environments
Mario P.
Last position:
Senior IT Project Manager / Program Lead – Network Strategy 2030 at ALDB GmbH
- Holistic responsibility for modernizing and expanding federal networks and upgrading critical data center and telecom infrastructure in the high-security agency environment of BDBOS
- Planning and management of the expansion of national BOS network infrastructure in the VS-NfD/KRITIS environment with technical decision authority at the architecture and component level (Cisco, Layer 2/3, WAN redundancy)
- Planning, tendering (EVB-IT/UVgO) and oversight of the upgrade of security-critical telecom infrastructure for emergency call 110/112 (ACD)
- Capacity planning, rack integration, structured cabling, power supply, cooling concept (CRAC/In-Row) and DCIM monitoring for data center expansion
- Building the IT department from scratch: structures, governance, processes, team recruiting, vendor selection and long-term IT strategy
- Planning and managing infrastructure and application migrations: migration strategies, batch planning, hypercare stabilization and rollback concepts
- Creating vendor-neutral specifications (telecom systems, signature solutions) according to EVB-IT and UVgO; contract award and vendor management
- Setting up a secure IT environment according to BSI basic protection, ISO 27001 and VS-NfD; developing IT security concepts and CMDB analyses
- Hands-on program leadership: decision papers for management and steering committees, risk management, reporting and change request control
Ashkan Z.
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Tan P.
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Mohammed A.
Last position:
Business Start-up and Continuing Education at Self-Employment
- Evaluation of further training options in the field of artificial intelligence
- Development of a business plan for self-employment in the AI sector
- Development of an offline chatbot for Excelsior GmbH
- Preparation for the "AWS Certified Solutions Architect – Associate" certification to expand cloud skills
Ritika S.
Last position:
AWmOpsRtKekEX(CPEliRenIEtN: CInEfoSrs.yDs,aHtaitAarcchhiiEtencetr(gAyW) S)
Global marketing analytics for Hitachi Energy as part of a global data modernization initiative aiming to enhance data retention, historical data availability and provide Eloqua's 2-year retention for remote interaction reporting and analytics.
Analyzed Eloqua's default retention policy and identified risk of data loss for records older than two years.
Designed and implemented historical data preservation strategy by creating transformed tables in the target data platform to archive older data while ensuring data quality dashboards.
Collaborated with the Power BI team to re-point dashboards from raw Eloqua imports to the newly created archival layer.
Leveraged Jira to track and manage data engineering tasks, bugs, and feature requests across Agile sprints; coordinated backlog prioritization and task assignment to align data pipeline development with business needs.
Power BI dashboard optimization:
Worked closely with business stakeholders to assess and understand reporting needs for reverse customer data.
Designed and implemented incremental refresh in Power BI to ensure daily updates without full data reloads.
Collaborated with Azure data engineers to optimize data processing and publication pipelines.
Stakeholder communication & data modeling:
Acted as liaison between Group Data Office and Technology Office to align data modelling standards.
Gathered requirements from data engineering team and participated in weekly status meetings to provide implementation updates and resolve blockers across teams in Germany, Poland, and India.
Documentation & quality assurance:
Prepared end-to-end technical design documentation, data flow diagrams, and Power BI audit guides for future reference.
Participated in UAT sessions with business users to validate data outputs and report accuracy.
Discover over 15,000 top freelancers
Statistics of experts using Amazon CloudWatch
Aggregated from the professional profiles of matched freelancers.
Experience
24 years (Germany: 16 years)

Position duration
1.9 years (Germany: 2 years)

Positions per freelancer
13 (Germany: 11)

Top business areas
Information Technology, Project Management, Business Intelligence

Top industries
Information Technology, Banking and Finance, Government and Administration

Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
86% (Germany: 91%)
Master's degree or higher
71% (Germany: 56%)
Doctorate
14% (Germany: 9%)

Certifications per freelancer
6 (Germany: 4)

Most common languages
German, English, Arabic

Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Frankfurt are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Frankfurt using Amazon CloudWatch
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Amazon CloudWatch experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Banking and Finance (86%)
- Government and Administration (71%)
- Automotive (57%)
- Healthcare (57%)
- Insurance (57%)
- Energy (43%)
- Transportation (43%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Monitoring on AWS
Amazon CloudWatch collects and visualizes metrics, logs, traces, events, and operational signals from AWS resources and applications. Companies use it to understand system health, detect incidents, investigate failures, and track service behavior without moving every signal into a separate monitoring product.
Core capabilities
CloudWatch specialists configure alarms, dashboards, log groups, metric filters, anomaly detection, and retention policies. They connect signals from services such as Amazon EC2, ECS, EKS, Lambda, RDS, API Gateway, and CloudFront, then turn raw telemetry into useful operational views. Strong work also covers tagging, access control, and cost-aware data collection.
Delivery areas
- Centralize application and infrastructure logs with CloudWatch Logs
- Create alarms and notification flows through Amazon SNS
- Build dashboards for production health, capacity, and service-level signals
- Use CloudWatch Events and EventBridge for operational automation
- Link metrics, logs, and traces for faster incident investigation
When specialists help
Companies often bring in freelance expertise during an AWS migration, a production launch, or an observability redesign. Outside support is also valuable when alarms are noisy, dashboards lack context, logs are expensive to retain, or teams need a consistent monitoring model across accounts and regions. In Frankfurt, specialists may work remotely or alongside local teams, depending on security and delivery requirements.
Connected AWS skills
Effective CloudWatch work depends on more than console configuration. Professionals commonly combine it with AWS Identity and Access Management, CloudTrail, X-Ray, EventBridge, Systems Manager, Terraform, CloudFormation, Kubernetes, container operations, and scripting. They should understand networking, serverless architectures, distributed systems, and incident response well enough to connect telemetry with real operational action.
What quality looks like
A strong professional defines signals around user impact rather than collecting data without purpose. They set meaningful thresholds, document alert ownership, separate symptoms from causes, and test notifications before production use. They also review ingestion and retention choices, protect sensitive log data, and leave behind dashboards and runbooks that internal teams can maintain. Frankfurt-based engagements may benefit from German and English communication, especially where local operations and remote AWS teams work together.
Frequently asked questions
Curious about Amazon CloudWatch? Here are the answers that come up again and again.
Amazon CloudWatch is AWS's native service for monitoring metrics, logs, events, and operational activity. Companies use it to create dashboards, trigger alarms, investigate incidents, and automate responses across cloud infrastructure and applications.
Amazon CloudWatch integrates directly with AWS services and usually requires less external collection setup in an AWS-first environment. Datadog offers broad cross-platform observability with a unified commercial experience, while Prometheus provides flexible, open-source metrics collection that often needs more configuration and surrounding tools.
A strong CloudWatch specialist should understand AWS Identity and Access Management, CloudTrail, X-Ray, EventBridge, Terraform, CloudFormation, and alerting through Amazon SNS. Experience with Kubernetes, Lambda, networking, distributed systems, and incident response is also useful.
The right level depends on the scope, not a fixed duration. A focused dashboard or alarm setup may need a specialist familiar with the relevant AWS services, while a multi-account observability redesign calls for someone who can shape architecture, security, automation, costs, and operating procedures.
Amazon CloudWatch work is often suitable for remote collaboration because configuration, reviews, and testing can happen through AWS accounts and shared documentation. On-site sessions in Frankfurt can still help when the engagement involves regulated environments, internal workshops, or close coordination with operations teams.
Ask the professional to explain how they would reduce noisy alarms, choose useful metrics, structure log groups, and protect sensitive data. A good CloudWatch specialist can show clear dashboards, documented alert logic, tested notification paths, and decisions linked to operational outcomes.
CloudWatch supports monitoring for Amazon ECS, Amazon EKS, Lambda, and the AWS services around them. The specialist may combine native metrics with application logs, embedded metrics, traces through X-Ray, and EventBridge rules to connect infrastructure signals with application behavior.
A CloudWatch professional may deliver dashboards, alarms, metric filters, log retention settings, notification workflows, infrastructure-as-code, and operational runbooks. The handover should explain signal meaning, escalation ownership, access requirements, and how the team can extend the setup safely.
The average hourly rate of freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects is 92 €, which corresponds to a daily rate of about 736 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects, 86% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects are German (100%), English (100%), and Arabic (14%).
The most common industries among freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects are Information Technology (100%), Banking and Finance (86%), and Government and Administration (71%).
The most common business areas among freelancers in Frankfurt, Germany who have used Amazon CloudWatch in their recent projects are Information Technology (100%), Project Management (71%), and Business Intelligence (57%).
Main locations of FRATCH Experts, who have recently used Amazon CloudWatch
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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