Apache Pulsar Consulting and Support Services
Unlock real-time insights with scalable, secure, and high-throughput event streaming, engineered and managed by Ksolves experts.
24×7 Support Services
Enterprise Assurance with SLA-Backed Support
Experienced Apache Pulsar Experts
Expert Apache Pulsar consulting and support for building scalable, fault-tolerant event streaming platforms with high availability and low latency.
Pulsar Architecture and Solution Design
We build end-to-end event streaming strategies and cluster architectures aligned with your enterprise goals. Our team assesses your infrastructure, designs broker and BookKeeper HA topologies, selects the right replication and subscription model, and delivers precise capacity planning to future-proof your Pulsar deployment.
Kafka and RabbitMQ to Apache Pulsar Migration
Our experts manage the full migration lifecycle from consumer group remapping and topic schema translation to subscription model alignment and phased cutover. Every step is validated for message-level data integrity so your workloads continue running without disruption throughout the transition.
Cluster Deployment and Configuration
We deploy production-ready Pulsar clusters across on-premises, cloud, and hybrid environments using Kubernetes manifests and Helm-based installation. Our engineers configure the Pulsar Proxy for client routing, tune BookKeeper bookie pools for optimal write and read performance, harden TLS and RBAC settings, and configure the full broker stack for secure, high-performance operations from day one.
AI/ML and Data Science Enablement
By integrating Pulsar as the real-time data backbone for AI/ML pipelines, our experts connect Spark MLlib, MLflow, and Flink to Pulsar-sourced feature stores and model feedback streams. Topic-level retention and schema versioning policies ensure reproducible training datasets and consistent model monitoring across the full ML lifecycle.
Pulsar Managed Services
Our managed services provide 24x7 cluster health monitoring, proactive consumer lag detection, and throughput capacity forecasting. Regular performance reviews, SLA reporting, and roadmap advisory sessions ensure your Pulsar environment stays optimized, reliable, and ahead of growing data streaming demands.
Data Integration and Pipeline Engineering
We integrate Pulsar across your data stack by configuring NiFi and Kafka Connect-compatible source and sink connectors, Spark and Flink via Pulsar IO, and Hive metastore setups using the Pulsar Hive connector. S3-compatible Pulsar client interfaces are migrated without requiring application code changes.
Data Lakehouse Architecture
We use Apache Pulsar as the real-time ingestion layer for cloud-native data lakehouses, integrating Apache Iceberg, Delta Lake, and Apache Hudi as downstream storage formats. Multi-tenant namespace design and schema evolution via Pulsar Schema Registry ensure your lakehouse scales cleanly as event data volumes grow.
Security and Data Governance
Our experts secure your Pulsar cluster with TLS mutual authentication, JWT and OAuth2 token-based authorization, Apache Ranger ACL policies, and KMS-based encryption for data at rest. GDPR-aligned audit logging and topic-level access controls ensure compliance with HIPAA, CCPA, and SOC 2 Type II requirements.
Health Check and Performance Audit
We analyze your Pulsar cluster across broker, BookKeeper, and ZooKeeper layers to surface security gaps, performance bottlenecks, and cost inefficiencies. The audit covers JVM tuning, partition strategy review, consumer group lag analysis, and tiered storage configuration, delivering a prioritized action plan to maximize reliability and throughput.
Data Analytics with Apache Pulsar
Our experts connect Pulsar to your analytics stack by integrating Apache Flink SQL, Apache Trino, and Spark Structured Streaming query engines directly against Pulsar topics. Apache Superset and Grafana dashboards are linked to Pulsar-sourced data so teams can query and visualize real-time event streams efficiently and at scale.
Monitoring with Managed Grafana
We instrument Prometheus-based metrics from Pulsar brokers, BookKeeper bookies, and ZooKeeper quorum nodes into custom Grafana dashboards built around your operational KPIs. Alerting rules for consumer lag, replication delays, and broker memory events are connected to PagerDuty, OpsGenie, and Slack for instant notification.
Version Upgrades and Patch Management
Our experts execute rolling Pulsar upgrades in the correct sequence: BookKeeper bookies first, then brokers and proxies. Each stage includes a full compatibility matrix assessment, pre-upgrade configuration backup, post-upgrade consumer validation, and a documented rollback plan to ensure zero risk to production message streams. ZooKeeper nodes are upgraded separately only when operationally required.
Pulsar Architecture and Solution Design
We build end-to-end event streaming strategies and cluster architectures aligned with your enterprise goals. Our team assesses your infrastructure, designs broker and BookKeeper HA topologies, selects the right replication and subscription model, and delivers precise capacity planning to future-proof your Pulsar deployment.
Kafka and RabbitMQ to Apache Pulsar Migration
Our experts manage the full migration lifecycle from consumer group remapping and topic schema translation to subscription model alignment and phased cutover. Every step is validated for message-level data integrity so your workloads continue running without disruption throughout the transition.
Cluster Deployment and Configuration
We deploy production-ready Pulsar clusters across on-premises, cloud, and hybrid environments using Kubernetes manifests and Helm-based installation. Our engineers configure the Pulsar Proxy for client routing, tune BookKeeper bookie pools for optimal write and read performance, harden TLS and RBAC settings, and configure the full broker stack for secure, high-performance operations from day one.
AI/ML and Data Science Enablement
By integrating Pulsar as the real-time data backbone for AI/ML pipelines, our experts connect Spark MLlib, MLflow, and Flink to Pulsar-sourced feature stores and model feedback streams. Topic-level retention and schema versioning policies ensure reproducible training datasets and consistent model monitoring across the full ML lifecycle.
Pulsar Managed Services
Our managed services provide 24x7 cluster health monitoring, proactive consumer lag detection, and throughput capacity forecasting. Regular performance reviews, SLA reporting, and roadmap advisory sessions ensure your Pulsar environment stays optimized, reliable, and ahead of growing data streaming demands.
Data Integration and Pipeline Engineering
We integrate Pulsar across your data stack by configuring NiFi and Kafka Connect-compatible source and sink connectors, Spark and Flink via Pulsar IO, and Hive metastore setups using the Pulsar Hive connector. S3-compatible Pulsar client interfaces are migrated without requiring application code changes.
Data Lakehouse Architecture
We use Apache Pulsar as the real-time ingestion layer for cloud-native data lakehouses, integrating Apache Iceberg, Delta Lake, and Apache Hudi as downstream storage formats. Multi-tenant namespace design and schema evolution via Pulsar Schema Registry ensure your lakehouse scales cleanly as event data volumes grow.
Security and Data Governance
Our experts secure your Pulsar cluster with TLS mutual authentication, JWT and OAuth2 token-based authorization, Apache Ranger ACL policies, and KMS-based encryption for data at rest. GDPR-aligned audit logging and topic-level access controls ensure compliance with HIPAA, CCPA, and SOC 2 Type II requirements.
Health Check and Performance Audit
We analyze your Pulsar cluster across broker, BookKeeper, and ZooKeeper layers to surface security gaps, performance bottlenecks, and cost inefficiencies. The audit covers JVM tuning, partition strategy review, consumer group lag analysis, and tiered storage configuration, delivering a prioritized action plan to maximize reliability and throughput.
Data Analytics with Apache Pulsar
Our experts connect Pulsar to your analytics stack by integrating Apache Flink SQL, Apache Trino, and Spark Structured Streaming query engines directly against Pulsar topics. Apache Superset and Grafana dashboards are linked to Pulsar-sourced data so teams can query and visualize real-time event streams efficiently and at scale.
Monitoring with Managed Grafana
We instrument Prometheus-based metrics from Pulsar brokers, BookKeeper bookies, and ZooKeeper quorum nodes into custom Grafana dashboards built around your operational KPIs. Alerting rules for consumer lag, replication delays, and broker memory events are connected to PagerDuty, OpsGenie, and Slack for instant notification.
Version Upgrades and Patch Management
Our experts execute rolling Pulsar upgrades in the correct sequence: BookKeeper bookies first, then brokers and proxies. Each stage includes a full compatibility matrix assessment, pre-upgrade configuration backup, post-upgrade consumer validation, and a documented rollback plan to ensure zero risk to production message streams. ZooKeeper nodes are upgraded separately only when operationally required.
Sub-10ms Latency
Stateless brokers with Apache BookKeeper's distributed log ensure strongly consistent, high-throughput messaging with sub-10ms latency, ideal for real-time workloads.
Tiered Storage
Offload older data to S3, GCS, or Azure Blob for cost efficiency while retaining seamless access without reconfiguration.
Geo-Replication
Supports synchronous BookKeeper replication and asynchronous broker-level replication with automatic failover across regions.
Multi-Tenancy
Tenants, namespaces, and ACLs provide secure, isolated environments on shared clusters.
Scalability
Decoupled architecture supports millions of topics without data reshuffling.
Kubernetes Ready
Cloud-native deployment with Kubernetes and unified access via Pulsar clients.
We deliver high-performance Apache Pulsar solutions for mission-critical, real-time data streaming across diverse industry verticals.
Healthcare
Retail & E-Commerce
Logistics and Supply Chain
Education
Financial Services
Manufacturing
Public Sector
Media and Entertainment
IT Industry
Telecom
How is Apache Pulsar different from Kafka or RabbitMQ?
Apache Pulsar uses a decoupled architecture (compute and storage separation via BookKeeper), supports multi-tenancy, and offers built-in geo-replication making it more flexible and scalable compared to traditional messaging systems.
Can you migrate from Kafka or RabbitMQ to Apache Pulsar without downtime?
Yes, migrations are executed using phased cutover strategies, parallel data pipelines, and validation checks to ensure zero data loss and minimal or no downtime.
Can you migrate from Kafka or RabbitMQ to Apache Pulsar without downtime?
Yes, migrations are executed using phased cutover strategies, parallel data pipelines, and validation checks to ensure zero data loss and minimal or no downtime.
Do you support cloud, on-premises, and hybrid Pulsar deployments?
Yes, Pulsar clusters can be deployed across cloud (AWS, Azure, GCP), on-premises, or hybrid environments using Kubernetes and Helm for flexible scalability.
How do you ensure high availability and fault tolerance in Pulsar?
High availability is achieved through broker load balancing, BookKeeper replication, multi-zone deployments, and automated failover mechanisms.
