JENNIFER APM

See application performance, transaction by transaction.

Monitor running transactions in real time, identify slow ones, and see where time is spent.

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JENNIFER transaction lifecycle: live requests stack by running time across Active Service instances; a completed request becomes one X-View dot; a selected slow dot opens /api/orders analysis, showing 25.9 seconds response time and 22.4 seconds SQL time. Vertical JENNIFER transaction lifecycle: red long running requests in Active Service, a completed request becoming an X-View dot, then /api/orders analysis with SQL taking most of the response time.
See JENNIFER in Action

WHY JENNIFER

Performance problems happen one transaction at a time.

Modern systems generate logs, metrics, traces, and infrastructure data. They all provide useful context. When a user experiences a slow or failed request, the problem shows up in an application transaction. JENNIFER starts there.

Start with the transaction that experienced the problem.

THE JENNIFER SIGNATURE EXPERIENCE

From live slowdown to deeper analysis.

Many live transactions become a response-time pattern. Choose the request that needs attention, then examine where its time was spent.

SEE IT LIVESPOT THE PATTERNDRILL DOWN
Sharp vector visual: six Active Service instance lanes show stacked running transactions from blue through green and orange to red, a centered connector shows requests completing, and X-View plots each completed transaction as a dot by time and response time LIVE TRANSACTIONS ACTIVE SERVICE 1 request completes 1 dot COMPLETED TRANSACTIONS X-VIEW Every dot is a transaction.
MANY COMPLETED TRANSACTIONSSELECT ONE PROBLEM TRANSACTION
03 / TRANSACTION ANALYSIS

Drill down to where the time was spent.

In the /api/orders example, SQL accounts for most of the response time.

RESPONSE TIME25,919 ms
SQL22,455 ms

The visual simplifies JENNIFER's Active Service Status and X-View behavior. The analysis values come from the captured /api/orders example. Actual product screens are shown below.

ACTUAL PRODUCT SCREENS

See JENNIFER in Action.

Explore the original product captures behind the simplified transaction lifecycle above.

01 / LIVE
Original JENNIFER Dashboard with Active Service Status at the upper right
Active Service StatusOpen original Dashboard capture ↗ 02 / COMPLETED
Original JENNIFER X-View capture showing completed transactions
X-ViewOpen original X-View capture ↗ 03 / ANALYZE
Original JENNIFER /api/orders transaction detail showing response time and SQL time
Transaction AnalysisOpen original /api/orders capture ↗

These captures illustrate the workflow; they do not establish that the screens show one continuous transaction.

WHAT THE WORKFLOW GIVES YOU

Know what is happening. Understand what changed.

01 / REAL TIME

Know what your application is processing right now.

See active transactions and identify requests that are taking unusually long.

Active Service Status

Concept illustration · 26 seconds · SilentActual product recording · Controlled demo traffic
02 / PATTERNS

Make performance problems visible.

Use X-View to recognize slow transactions and unusual response-time patterns.

X-View

Concept illustration · 26 seconds · SilentActual product recording · SQL and external HTTP cases
03 / DETAILS

Understand where the time went.

Inspect an individual transaction across application methods, SQL, external calls, and errors.

SUPPORTED ENVIRONMENTS

Monitor the applications you already run.

JENNIFER supports major platforms used for business-critical web applications. Confirm runtime and version coverage for your environment during evaluation.

Explore JENNIFER platforms

APPLICATION PLATFORMS

Java.NETPHPPythonNode.js

MODERN APPLICATION ENVIRONMENTS

KubernetesMicroservices

KUBERNETES & MICROSERVICES

The application is still the center. Kubernetes provides the context around it.

Applications run as services. Transactions move across them. Kubernetes provides the runtime context.

Illustrative user request follows a transaction path through Customer PHP, Order Java, Inventory Node.js, Payment .NET Core, and Shipping Python services. Pod, Container, Node, Resource, and Event appear below as Kubernetes runtime context. Vertical illustrative flow from one user request through five application services, followed by Kubernetes runtime context: Pod, Container, Node, Resource, and Event.

ACTUAL PRODUCT PROOF

From the transaction path to its runtime context

MSA TRANSACTION FLOW

Follow a transaction across services.

See how a single request moves across services, databases, and external calls.

/api/products/9429gatewayproductinventoryPostgreSQL
Cropped actual JENNIFER MSA view showing gateway-service, product-service, inventory-service and PostgreSQL calls.View full screen ↗

KUBERNETES RUNTIME TOPOLOGY

See where those services actually run.

Connect the application service to the Kubernetes resources and runtime behind it.

ServiceDeploymentPodContainer / APM
Cropped actual JENNIFER topology showing mall-app Service, Deployment, Pod, Container and APM tag.View full screen ↗

Separate product captures show the transaction view and runtime topology; they are not one continuous request in the same environment.

Actual product recording · 19 seconds · Silent

A separate recorded walkthrough of an MSA request and its Kubernetes runtime context.

JENNIFER INSIGHTS

AI-assisted analysis, grounded in application performance data.

Use selected transaction details, profiles, errors, stack traces, response times, and SQL / external-call context to support investigation. Review AI suggestions against the source APM data.

Illustrative flow: JENNIFER APM transaction data and other available evidence become selected performance context for AI-assisted suggestions, which an operator reviews against the source data. Vertical illustrative flow from JENNIFER APM transaction data to performance context to AI-assisted analysis for operator review.

JENNIFERSOFT / COMPANY TRUST

APM expertise since 2005.

JenniferSoft has focused on APM since 2005. Experience with customers in South Korea and Japan has shaped our product expertise and our sales, technical support, and marketing capabilities.

APM EXPERIENCESince 2005

Continued product development focused on APM.

KOREA1,700+ customers

JENNIFER customers in South Korea.

JAPAN300+ customers

JENNIFER customers in Japan.

JENNIFER IN USE AROUND THE WORLD

South KoreaJapanVietnamSingaporeMalaysiaUnited StatesChinaThailandIndonesia
About JenniferSoft

FOR POTENTIAL PARTNERS

Bring JENNIFER to your market.

Considering JENNIFER for your market? Explore the product, the customers it serves, and how JenniferSoft can support your sales and technical work.

Explore Partnership
01A focused APM productTransaction-first monitoring and analysis with a clear product story.
02A clear customer fitFor enterprises running business-critical web applications where performance matters.
03Support from JenniferSoftProduct knowledge, technical help, sales enablement, and marketing resources.

JENNIFER APM

See how JENNIFER approaches application performance, transaction by transaction.

See how JENNIFER connects live transaction monitoring to the analysis of slow requests.

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Interested in partnership? Explore Partnership →

JENNIFER product video