k8sgpt/pkg/analysis/analysis.go
Matthis 3eec9bbb05
feat: add stats option to analyze command for performance insights (#1237)
* feat: add stats option to analyze command for performance insights

Introduced a new feature to the analyze command that enables users to print detailed performance statistics of each analyzer. This enhancement aids in debugging and understanding the time taken by various components during analysis, providing valuable insights for performance optimization.

Signed-off-by: Matthis Holleville <matthish29@gmail.com>

* feat: enhance analysis command with statistics option

Refactored the analysis command to support an enhanced statistics option, enabling users to opt-in for detailed performance metrics of the analysis process. This change introduces a more flexible approach to handling statistics, allowing for a clearer separation between the analysis output and performance metrics, thereby improving the usability and insights provided to the user.

Signed-off-by: Matthis Holleville <matthish29@gmail.com>

---------

Signed-off-by: Matthis Holleville <matthish29@gmail.com>
Co-authored-by: Alex Jones <alexsimonjones@gmail.com>
Co-authored-by: Aris Boutselis <arisboutselis08@gmail.com>
2024-10-30 13:58:18 +00:00

425 lines
11 KiB
Go

/*
Copyright 2023 The K8sGPT Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package analysis
import (
"context"
"encoding/base64"
"errors"
"fmt"
"strings"
"sync"
"time"
"github.com/fatih/color"
openapi_v2 "github.com/google/gnostic/openapiv2"
"github.com/k8sgpt-ai/k8sgpt/pkg/ai"
"github.com/k8sgpt-ai/k8sgpt/pkg/analyzer"
"github.com/k8sgpt-ai/k8sgpt/pkg/cache"
"github.com/k8sgpt-ai/k8sgpt/pkg/common"
"github.com/k8sgpt-ai/k8sgpt/pkg/custom"
"github.com/k8sgpt-ai/k8sgpt/pkg/kubernetes"
"github.com/k8sgpt-ai/k8sgpt/pkg/util"
"github.com/schollz/progressbar/v3"
"github.com/spf13/viper"
)
type Analysis struct {
Context context.Context
Filters []string
Client *kubernetes.Client
Language string
AIClient ai.IAI
Results []common.Result
Errors []string
Namespace string
LabelSelector string
Cache cache.ICache
Explain bool
MaxConcurrency int
AnalysisAIProvider string // The name of the AI Provider used for this analysis
WithDoc bool
WithStats bool
Stats []common.AnalysisStats
}
type (
AnalysisStatus string
AnalysisErrors []string
)
const (
StateOK AnalysisStatus = "OK"
StateProblemDetected AnalysisStatus = "ProblemDetected"
)
type JsonOutput struct {
Provider string `json:"provider"`
Errors AnalysisErrors `json:"errors"`
Status AnalysisStatus `json:"status"`
Problems int `json:"problems"`
Results []common.Result `json:"results"`
}
func NewAnalysis(
backend string,
language string,
filters []string,
namespace string,
labelSelector string,
noCache bool,
explain bool,
maxConcurrency int,
withDoc bool,
interactiveMode bool,
httpHeaders []string,
withStats bool,
) (*Analysis, error) {
// Get kubernetes client from viper.
kubecontext := viper.GetString("kubecontext")
kubeconfig := viper.GetString("kubeconfig")
client, err := kubernetes.NewClient(kubecontext, kubeconfig)
if err != nil {
return nil, fmt.Errorf("initialising kubernetes client: %w", err)
}
// Load remote cache if it is configured.
cache, err := cache.GetCacheConfiguration()
if err != nil {
return nil, err
}
if noCache {
cache.DisableCache()
}
a := &Analysis{
Context: context.Background(),
Filters: filters,
Client: client,
Language: language,
Namespace: namespace,
LabelSelector: labelSelector,
Cache: cache,
Explain: explain,
MaxConcurrency: maxConcurrency,
WithDoc: withDoc,
WithStats: withStats,
}
if !explain {
// Return early if AI use was not requested.
return a, nil
}
var configAI ai.AIConfiguration
if err := viper.UnmarshalKey("ai", &configAI); err != nil {
return nil, err
}
if len(configAI.Providers) == 0 {
return nil, errors.New("AI provider not specified in configuration. Please run k8sgpt auth")
}
// Backend string will have high priority than a default provider
// Hence, use the default provider only if the backend is not specified by the user.
if configAI.DefaultProvider != "" && backend == "" {
backend = configAI.DefaultProvider
}
if backend == "" {
backend = "openai"
}
var aiProvider ai.AIProvider
for _, provider := range configAI.Providers {
if backend == provider.Name {
aiProvider = provider
break
}
}
if aiProvider.Name == "" {
return nil, fmt.Errorf("AI provider %s not specified in configuration. Please run k8sgpt auth", backend)
}
aiClient := ai.NewClient(aiProvider.Name)
customHeaders := util.NewHeaders(httpHeaders)
aiProvider.CustomHeaders = customHeaders
if err := aiClient.Configure(&aiProvider); err != nil {
return nil, err
}
a.AIClient = aiClient
a.AnalysisAIProvider = aiProvider.Name
return a, nil
}
func (a *Analysis) CustomAnalyzersAreAvailable() bool {
var customAnalyzers []custom.CustomAnalyzer
if err := viper.UnmarshalKey("custom_analyzers", &customAnalyzers); err != nil {
return false
}
return len(customAnalyzers) > 0
}
func (a *Analysis) RunCustomAnalysis() {
var customAnalyzers []custom.CustomAnalyzer
if err := viper.UnmarshalKey("custom_analyzers", &customAnalyzers); err != nil {
a.Errors = append(a.Errors, err.Error())
return
}
semaphore := make(chan struct{}, a.MaxConcurrency)
var wg sync.WaitGroup
var mutex sync.Mutex
for _, cAnalyzer := range customAnalyzers {
wg.Add(1)
semaphore <- struct{}{}
go func(analyzer custom.CustomAnalyzer, wg *sync.WaitGroup, semaphore chan struct{}) {
defer wg.Done()
canClient, err := custom.NewClient(cAnalyzer.Connection)
if err != nil {
mutex.Lock()
a.Errors = append(a.Errors, fmt.Sprintf("Client creation error for %s analyzer", cAnalyzer.Name))
mutex.Unlock()
return
}
result, err := canClient.Run()
if result.Kind == "" {
// for custom analyzer name, we must use a lowercase RFC 1123 subdomain must consist of lower case alphanumeric characters, '-' or '.',
//and must start and end with an alphanumeric character (e.g. 'example.com',
//regex used for validation is '[a-z0-9]([-a-z0-9]*[a-z0-9])?(\\.[a-z0-9]([-a-z0-9]*[a-z0-9])?)*')
result.Kind = cAnalyzer.Name
}
if err != nil {
mutex.Lock()
a.Errors = append(a.Errors, fmt.Sprintf("[%s] %s", cAnalyzer.Name, err))
mutex.Unlock()
} else {
mutex.Lock()
a.Results = append(a.Results, result)
mutex.Unlock()
}
<-semaphore
}(cAnalyzer, &wg, semaphore)
}
wg.Wait()
}
func (a *Analysis) RunAnalysis() {
activeFilters := viper.GetStringSlice("active_filters")
coreAnalyzerMap, analyzerMap := analyzer.GetAnalyzerMap()
// we get the openapi schema from the server only if required by the flag "with-doc"
openapiSchema := &openapi_v2.Document{}
if a.WithDoc {
var openApiErr error
openapiSchema, openApiErr = a.Client.Client.Discovery().OpenAPISchema()
if openApiErr != nil {
a.Errors = append(a.Errors, fmt.Sprintf("[KubernetesDoc] %s", openApiErr))
}
}
analyzerConfig := common.Analyzer{
Client: a.Client,
Context: a.Context,
Namespace: a.Namespace,
LabelSelector: a.LabelSelector,
AIClient: a.AIClient,
OpenapiSchema: openapiSchema,
}
semaphore := make(chan struct{}, a.MaxConcurrency)
var wg sync.WaitGroup
var mutex sync.Mutex
// if there are no filters selected and no active_filters then run coreAnalyzer
if len(a.Filters) == 0 && len(activeFilters) == 0 {
for name, analyzer := range coreAnalyzerMap {
wg.Add(1)
semaphore <- struct{}{}
go a.executeAnalyzer(analyzer, name, analyzerConfig, semaphore, &wg, &mutex)
}
wg.Wait()
return
}
// if the filters flag is specified
if len(a.Filters) != 0 {
for _, filter := range a.Filters {
if analyzer, ok := analyzerMap[filter]; ok {
semaphore <- struct{}{}
wg.Add(1)
go a.executeAnalyzer(analyzer, filter, analyzerConfig, semaphore, &wg, &mutex)
} else {
a.Errors = append(a.Errors, fmt.Sprintf("\"%s\" filter does not exist. Please run k8sgpt filters list.", filter))
}
}
wg.Wait()
return
}
// use active_filters
for _, filter := range activeFilters {
if analyzer, ok := analyzerMap[filter]; ok {
semaphore <- struct{}{}
wg.Add(1)
go a.executeAnalyzer(analyzer, filter, analyzerConfig, semaphore, &wg, &mutex)
}
}
wg.Wait()
}
func (a *Analysis) executeAnalyzer(analyzer common.IAnalyzer, filter string, analyzerConfig common.Analyzer, semaphore chan struct{}, wg *sync.WaitGroup, mutex *sync.Mutex) {
defer wg.Done()
var startTime time.Time
var elapsedTime time.Duration
// Start the timer
if a.WithStats {
startTime = time.Now()
}
// Run the analyzer
results, err := analyzer.Analyze(analyzerConfig)
// Measure the time taken
if a.WithStats {
elapsedTime = time.Since(startTime)
}
stat := common.AnalysisStats{
Analyzer: filter,
DurationTime: elapsedTime,
}
mutex.Lock()
defer mutex.Unlock()
if err != nil {
if a.WithStats {
a.Stats = append(a.Stats, stat)
}
a.Errors = append(a.Errors, fmt.Sprintf("[%s] %s", filter, err))
} else {
if a.WithStats {
a.Stats = append(a.Stats, stat)
}
a.Results = append(a.Results, results...)
}
<-semaphore
}
func (a *Analysis) GetAIResults(output string, anonymize bool) error {
if len(a.Results) == 0 {
return nil
}
var bar *progressbar.ProgressBar
if output != "json" {
bar = progressbar.Default(int64(len(a.Results)))
}
for index, analysis := range a.Results {
var texts []string
for _, failure := range analysis.Error {
if anonymize {
for _, s := range failure.Sensitive {
failure.Text = util.ReplaceIfMatch(failure.Text, s.Unmasked, s.Masked)
}
}
texts = append(texts, failure.Text)
}
promptTemplate := ai.PromptMap["default"]
// If the resource `Kind` comes from an "integration plugin",
// maybe a customized prompt template will be involved.
if prompt, ok := ai.PromptMap[analysis.Kind]; ok {
promptTemplate = prompt
}
result, err := a.getAIResultForSanitizedFailures(texts, promptTemplate)
if err != nil {
// FIXME: can we avoid checking if output is json multiple times?
// maybe implement the progress bar better?
if output != "json" {
_ = bar.Exit()
}
// Check for exhaustion.
if strings.Contains(err.Error(), "status code: 429") {
return fmt.Errorf("exhausted API quota for AI provider %s: %v", a.AIClient.GetName(), err)
}
return fmt.Errorf("failed while calling AI provider %s: %v", a.AIClient.GetName(), err)
}
if anonymize {
for _, failure := range analysis.Error {
for _, s := range failure.Sensitive {
result = strings.ReplaceAll(result, s.Masked, s.Unmasked)
}
}
}
analysis.Details = result
if output != "json" {
_ = bar.Add(1)
}
a.Results[index] = analysis
}
return nil
}
func (a *Analysis) getAIResultForSanitizedFailures(texts []string, promptTmpl string) (string, error) {
inputKey := strings.Join(texts, " ")
// Check for cached data.
// TODO(bwplotka): This might depend on model too (or even other client configuration pieces), fix it in later PRs.
cacheKey := util.GetCacheKey(a.AIClient.GetName(), a.Language, inputKey)
if !a.Cache.IsCacheDisabled() && a.Cache.Exists(cacheKey) {
response, err := a.Cache.Load(cacheKey)
if err != nil {
return "", err
}
if response != "" {
output, err := base64.StdEncoding.DecodeString(response)
if err == nil {
return string(output), nil
}
color.Red("error decoding cached data; ignoring cache item: %v", err)
}
}
// Process template.
prompt := fmt.Sprintf(strings.TrimSpace(promptTmpl), a.Language, inputKey)
response, err := a.AIClient.GetCompletion(a.Context, prompt)
if err != nil {
return "", err
}
if err = a.Cache.Store(cacheKey, base64.StdEncoding.EncodeToString([]byte(response))); err != nil {
color.Red("error storing value to cache; value won't be cached: %v", err)
}
return response, nil
}
func (a *Analysis) Close() {
if a.AIClient == nil {
return
}
a.AIClient.Close()
}